ia-tictactoe.ipynb

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   "source": [
    "from kaggle_environments import make\n",
    "from copy import deepcopy\n",
    "import math\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import time"
   ]
  },
  {
   "cell_type": "markdown",
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   "source": [
    "## Algoritmo MinMax"
   ]
  },
  {
   "cell_type": "markdown",
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   },
   "source": [
    "Testando o algoritmo MinMax para a profundidade máxima (9) contra um player reativo"
   ]
  },
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   "source": [
    "vai_ganhar = lambda x, y: 1 if x == y else -1\n",
    "inverte = lambda x: 1 if x==2 else 2"
   ]
  },
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    "def isFinal(tabuleiro):\n",
    "    # checa colunas\n",
    "    for i in range(3):\n",
    "        if tabuleiro[i] == tabuleiro[i + 3] == tabuleiro[i + 6] and tabuleiro[i] != 0:\n",
    "            return True, tabuleiro[i]\n",
    "\n",
    "    # checa linhas\n",
    "    for i in range(0, 9, 3):\n",
    "        if tabuleiro[i] == tabuleiro[i + 1] == tabuleiro[i + 2] and tabuleiro[i] != 0:\n",
    "            return True, tabuleiro[i]\n",
    "\n",
    "    # checa diagonais (as duas)\n",
    "    if (tabuleiro[0] == tabuleiro[4] == tabuleiro[8] or tabuleiro[2] == tabuleiro[4] == tabuleiro[6]) and tabuleiro[\n",
    "        4] != 0:\n",
    "        return True, tabuleiro[4]\n",
    "\n",
    "    return False, None"
   ]
  },
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   "execution_count": 30,
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   "source": [
    "def quaseVitoria(tabuleiro, player):\n",
    "    soma = 0\n",
    "    # checa colunas não completas\n",
    "    for i in range(3):\n",
    "        if (tabuleiro[i] == tabuleiro[i + 3] and tabuleiro[i] != 0) or (\n",
    "                tabuleiro[i + 6] == tabuleiro[i + 3] and tabuleiro[i + 6] != 0) or (\n",
    "                tabuleiro[i] == tabuleiro[i + 6] and tabuleiro[i + 6] != 0):\n",
    "            if tabuleiro[i] == 0:\n",
    "                soma += vai_ganhar(tabuleiro[i + 3], player)\n",
    "            if tabuleiro[i + 3] == 0:\n",
    "                soma += vai_ganhar(tabuleiro[i], player)\n",
    "            if tabuleiro[i + 6] == 0:\n",
    "                soma += vai_ganhar(tabuleiro[i], player)\n",
    "\n",
    "    # checa linhas não completas\n",
    "    for i in range(0, 9, 3):\n",
    "        if (tabuleiro[i] == tabuleiro[i + 1] and tabuleiro[i] != 0) or (\n",
    "                tabuleiro[i + 2] == tabuleiro[i + 1] and tabuleiro[i + 2] != 0) or (\n",
    "                tabuleiro[i] == tabuleiro[i + 2] and tabuleiro[i + 2] != 0):\n",
    "            if tabuleiro[i] == 0:\n",
    "                soma += vai_ganhar(tabuleiro[i + 1], player)\n",
    "            if tabuleiro[i + 1] == 0:\n",
    "                soma += vai_ganhar(tabuleiro[i], player)\n",
    "            if tabuleiro[i + 2] == 0:\n",
    "                soma += vai_ganhar(tabuleiro[i], player)\n",
    "\n",
    "    # checa diagonal \\ não completa\n",
    "    if (tabuleiro[0] == tabuleiro[4] and tabuleiro[0] != 0) or (tabuleiro[0] == tabuleiro[8] and tabuleiro[0] != 0) or (\n",
    "            tabuleiro[8] == tabuleiro[4] and tabuleiro[4] != 0):\n",
    "        if tabuleiro[0] == 0:\n",
    "            soma += vai_ganhar(tabuleiro[4], player)\n",
    "        elif tabuleiro[4] == 0:\n",
    "            soma += vai_ganhar(tabuleiro[0], player)\n",
    "        elif tabuleiro[8] == 0:\n",
    "            soma += vai_ganhar(tabuleiro[0], player)\n",
    "\n",
    "    # checa diagonal / não completa\n",
    "    if (tabuleiro[2] == tabuleiro[4] and tabuleiro[2] != 0) or (tabuleiro[2] == tabuleiro[6] and tabuleiro[2] != 0) or (\n",
    "            tabuleiro[6] == tabuleiro[4] and tabuleiro[4] != 0):\n",
    "        if tabuleiro[2] == 0:\n",
    "            soma += vai_ganhar(tabuleiro[4], player)\n",
    "        elif tabuleiro[4] == 0:\n",
    "            soma += vai_ganhar(tabuleiro[2], player)\n",
    "        elif tabuleiro[6] == 0:\n",
    "            soma += vai_ganhar(tabuleiro[2], player)\n",
    "\n",
    "    return soma"
   ]
  },
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   "source": [
    "def f_utilidade(tabuleiro,player):\n",
    "    final,i = isFinal(tabuleiro)\n",
    "    soma=0\n",
    "    if final:\n",
    "        if i==player:\n",
    "            soma+=100000\n",
    "        else:\n",
    "            soma+=-100000\n",
    "    return quaseVitoria(tabuleiro,player)+soma"
   ]
  },
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   "source": [
    "def sucessores(tabuleiro,player):\n",
    "    success = list()\n",
    "    for i in range(len(tabuleiro)):\n",
    "        if tabuleiro[i]==0:\n",
    "            est = deepcopy(tabuleiro)\n",
    "            est[i] = player\n",
    "            success.append((est,i))\n",
    "    return success"
   ]
  },
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   "source": [
    "def max_value(tabuleiro, p, player,acao):\n",
    "    if p == 0 or isFinal(tabuleiro)[0]:\n",
    "        return f_utilidade(tabuleiro,player), acao\n",
    "    v = -math.inf\n",
    "    for s,op in sucessores(tabuleiro, player):\n",
    "        novo,_ = min_value(s, p-1,inverte(player),op)\n",
    "        if novo>v:\n",
    "            v = novo\n",
    "            acao = op\n",
    "    return v, acao\n",
    "\n",
    "\n",
    "def min_value(tabuleiro, p, player, acao):\n",
    "    if p == 0 or isFinal(tabuleiro)[0]:\n",
    "        return f_utilidade(tabuleiro,inverte(player)), acao\n",
    "    v = math.inf\n",
    "    for s,op in sucessores(tabuleiro, player):\n",
    "        novo,_ = max_value(s, p-1, inverte(player),op)\n",
    "        if novo<v:\n",
    "            v = novo\n",
    "            acao = op\n",
    "    return v, acao"
   ]
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   "source": [
    "def my_agent(obs,reward):\n",
    "    p = 9\n",
    "    player = obs['mark']\n",
    "    v,acao = max_value(obs['board'],p,player,None)\n",
    "    return acao"
   ]
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       "<iframe srcdoc=\"<!--\n",
       "  Copyright 2020 Kaggle Inc\n",
       "\n",
       "  Licensed under the Apache License, Version 2.0 (the &quot;License&quot;);\n",
       "  you may not use this file except in compliance with the License.\n",
       "  You may obtain a copy of the License at\n",
       "\n",
       "      http://www.apache.org/licenses/LICENSE-2.0\n",
       "\n",
       "  Unless required by applicable law or agreed to in writing, software\n",
       "  distributed under the License is distributed on an &quot;AS IS&quot; BASIS,\n",
       "  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
       "  See the License for the specific language governing permissions and\n",
       "  limitations under the License.\n",
       "-->\n",
       "<!DOCTYPE html>\n",
       "<html lang=&quot;en&quot;>\n",
       "  <head>\n",
       "    <title>Kaggle Simulation Player</title>\n",
       "    <meta name=&quot;viewport&quot; content=&quot;width=device-width,initial-scale=1&quot; />\n",
       "    <link\n",
       "      rel=&quot;stylesheet&quot;\n",
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       "      crossorigin=&quot;anonymous&quot;\n",
       "    />\n",
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       "      html,\n",
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       "        height: 100%;\n",
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       "        image-rendering: pixelated;\n",
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       "      }\n",
       "    </style>\n",
       "    <script src=&quot;https://unpkg.com/preact@10.0.1/dist/preact.umd.js&quot;></script>\n",
       "    <script src=&quot;https://unpkg.com/preact@10.0.1/hooks/dist/hooks.umd.js&quot;></script>\n",
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       "    </script>\n",
       "    <script src=&quot;https://unpkg.com/styled-components@3.5.0-0/dist/styled-components.min.js&quot;></script>\n",
       "  </head>\n",
       "  <body>\n",
       "    <script>\n",
       "      \n",
       "window.kaggle = {\n",
       "  &quot;debug&quot;: false,\n",
       "  &quot;playing&quot;: true,\n",
       "  &quot;step&quot;: 0,\n",
       "  &quot;controls&quot;: true,\n",
       "  &quot;environment&quot;: {\n",
       "    &quot;id&quot;: &quot;6892159e-d979-11ed-8eb9-0242ac130202&quot;,\n",
       "    &quot;name&quot;: &quot;tictactoe&quot;,\n",
       "    &quot;title&quot;: &quot;Tic Tac Toe&quot;,\n",
       "    &quot;description&quot;: &quot;Classic Tic Tac Toe&quot;,\n",
       "    &quot;version&quot;: &quot;1.0.0&quot;,\n",
       "    &quot;configuration&quot;: {\n",
       "      &quot;actTimeout&quot;: 1000,\n",
       "      &quot;agentTimeout&quot;: 1000,\n",
       "      &quot;runTimeout&quot;: 2000,\n",
       "      &quot;episodeSteps&quot;: 10\n",
       "    },\n",
       "    &quot;specification&quot;: {\n",
       "      &quot;action&quot;: {\n",
       "        &quot;description&quot;: &quot;Position to place a mark on the board.&quot;,\n",
       "        &quot;type&quot;: &quot;integer&quot;,\n",
       "        &quot;minimum&quot;: 0,\n",
       "        &quot;maximum&quot;: 8,\n",
       "        &quot;default&quot;: 0\n",
       "      },\n",
       "      &quot;agents&quot;: [\n",
       "        2\n",
       "      ],\n",
       "      &quot;configuration&quot;: {\n",
       "        &quot;episodeSteps&quot;: {\n",
       "          &quot;description&quot;: &quot;Maximum number of steps in the episode.&quot;,\n",
       "          &quot;type&quot;: &quot;integer&quot;,\n",
       "          &quot;minimum&quot;: 1,\n",
       "          &quot;default&quot;: 10\n",
       "        },\n",
       "        &quot;actTimeout&quot;: {\n",
       "          &quot;description&quot;: &quot;Maximum runtime (seconds) to obtain an action from an agent.&quot;,\n",
       "          &quot;type&quot;: &quot;number&quot;,\n",
       "          &quot;minimum&quot;: 0,\n",
       "          &quot;default&quot;: 1\n",
       "        },\n",
       "        &quot;runTimeout&quot;: {\n",
       "          &quot;description&quot;: &quot;Maximum runtime (seconds) of an episode (not necessarily DONE).&quot;,\n",
       "          &quot;type&quot;: &quot;number&quot;,\n",
       "          &quot;minimum&quot;: 0,\n",
       "          &quot;default&quot;: 1200\n",
       "        },\n",
       "        &quot;agentTimeout&quot;: {\n",
       "          &quot;description&quot;: &quot;Obsolete field kept for backwards compatibility, please use observation.remainingOverageTime.&quot;,\n",
       "          &quot;type&quot;: &quot;number&quot;,\n",
       "          &quot;minimum&quot;: 0,\n",
       "          &quot;default&quot;: 2\n",
       "        }\n",
       "      },\n",
       "      &quot;info&quot;: {},\n",
       "      &quot;observation&quot;: {\n",
       "        &quot;remainingOverageTime&quot;: {\n",
       "          &quot;description&quot;: &quot;Total remaining banked time (seconds) that can be used in excess of per-step actTimeouts -- agent is disqualified with TIMEOUT status when this drops below 0.&quot;,\n",
       "          &quot;shared&quot;: false,\n",
       "          &quot;type&quot;: &quot;number&quot;,\n",
       "          &quot;minimum&quot;: 0,\n",
       "          &quot;default&quot;: 2\n",
       "        },\n",
       "        &quot;step&quot;: {\n",
       "          &quot;description&quot;: &quot;Current step within the episode.&quot;,\n",
       "          &quot;type&quot;: &quot;integer&quot;,\n",
       "          &quot;shared&quot;: true,\n",
       "          &quot;minimum&quot;: 0,\n",
       "          &quot;default&quot;: 0\n",
       "        },\n",
       "        &quot;board&quot;: {\n",
       "          &quot;description&quot;: &quot;Serialized 3x3 grid. 0 = Empty, 1 = X, 2 = O&quot;,\n",
       "          &quot;type&quot;: &quot;array&quot;,\n",
       "          &quot;shared&quot;: true,\n",
       "          &quot;default&quot;: [\n",
       "            0,\n",
       "            0,\n",
       "            0,\n",
       "            0,\n",
       "            0,\n",
       "            0,\n",
       "            0,\n",
       "            0,\n",
       "            0\n",
       "          ],\n",
       "          &quot;minItems&quot;: 9,\n",
       "          &quot;maxItems&quot;: 9\n",
       "        },\n",
       "        &quot;mark&quot;: {\n",
       "          &quot;description&quot;: &quot;Mark for the agent to use&quot;,\n",
       "          &quot;defaults&quot;: [\n",
       "            1,\n",
       "            2\n",
       "          ],\n",
       "          &quot;enum&quot;: [\n",
       "            1,\n",
       "            2\n",
       "          ]\n",
       "        }\n",
       "      },\n",
       "      &quot;reward&quot;: {\n",
       "        &quot;description&quot;: &quot;-1 = Lost, 0 = Draw/Ongoing, 1 = Won&quot;,\n",
       "        &quot;enum&quot;: [\n",
       "          -1,\n",
       "          0,\n",
       "          1\n",
       "        ],\n",
       "        &quot;default&quot;: 0,\n",
       "        &quot;type&quot;: [\n",
       "          &quot;number&quot;,\n",
       "          &quot;null&quot;\n",
       "        ]\n",
       "      }\n",
       "    },\n",
       "    &quot;steps&quot;: [\n",
       "      [\n",
       "        {\n",
       "          &quot;action&quot;: 0,\n",
       "          &quot;reward&quot;: 0,\n",
       "          &quot;info&quot;: {},\n",
       "          &quot;observation&quot;: {\n",
       "            &quot;remainingOverageTime&quot;: 2,\n",
       "            &quot;step&quot;: 0,\n",
       "            &quot;board&quot;: [\n",
       "              0,\n",
       "              0,\n",
       "              0,\n",
       "              0,\n",
       "              0,\n",
       "              0,\n",
       "              0,\n",
       "              0,\n",
       "              0\n",
       "            ],\n",
       "            &quot;mark&quot;: 1\n",
       "          },\n",
       "          &quot;status&quot;: &quot;ACTIVE&quot;\n",
       "        },\n",
       "        {\n",
       "          &quot;action&quot;: 0,\n",
       "          &quot;reward&quot;: 0,\n",
       "          &quot;info&quot;: {},\n",
       "          &quot;observation&quot;: {\n",
       "            &quot;remainingOverageTime&quot;: 2,\n",
       "            &quot;mark&quot;: 2\n",
       "          },\n",
       "          &quot;status&quot;: &quot;INACTIVE&quot;\n",
       "        }\n",
       "      ],\n",
       "      [\n",
       "        {\n",
       "          &quot;action&quot;: 0,\n",
       "          &quot;reward&quot;: 0,\n",
       "          &quot;info&quot;: {},\n",
       "          &quot;observation&quot;: {\n",
       "            &quot;remainingOverageTime&quot;: 2,\n",
       "            &quot;step&quot;: 1,\n",
       "            &quot;board&quot;: [\n",
       "              1,\n",
       "              0,\n",
       "              0,\n",
       "              0,\n",
       "              0,\n",
       "              0,\n",
       "              0,\n",
       "              0,\n",
       "              0\n",
       "            ],\n",
       "            &quot;mark&quot;: 1\n",
       "          },\n",
       "          &quot;status&quot;: &quot;INACTIVE&quot;\n",
       "        },\n",
       "        {\n",
       "          &quot;action&quot;: 0,\n",
       "          &quot;reward&quot;: 0,\n",
       "          &quot;info&quot;: {},\n",
       "          &quot;observation&quot;: {\n",
       "            &quot;remainingOverageTime&quot;: 2,\n",
       "            &quot;mark&quot;: 2\n",
       "          },\n",
       "          &quot;status&quot;: &quot;ACTIVE&quot;\n",
       "        }\n",
       "      ],\n",
       "      [\n",
       "        {\n",
       "          &quot;action&quot;: 0,\n",
       "          &quot;reward&quot;: 0,\n",
       "          &quot;info&quot;: {},\n",
       "          &quot;observation&quot;: {\n",
       "            &quot;remainingOverageTime&quot;: 2,\n",
       "            &quot;step&quot;: 2,\n",
       "            &quot;board&quot;: [\n",
       "              1,\n",
       "              0,\n",
       "              0,\n",
       "              0,\n",
       "              0,\n",
       "              2,\n",
       "              0,\n",
       "              0,\n",
       "              0\n",
       "            ],\n",
       "            &quot;mark&quot;: 1\n",
       "          },\n",
       "          &quot;status&quot;: &quot;ACTIVE&quot;\n",
       "        },\n",
       "        {\n",
       "          &quot;action&quot;: 5,\n",
       "          &quot;reward&quot;: 0,\n",
       "          &quot;info&quot;: {},\n",
       "          &quot;observation&quot;: {\n",
       "            &quot;remainingOverageTime&quot;: 2,\n",
       "            &quot;mark&quot;: 2\n",
       "          },\n",
       "          &quot;status&quot;: &quot;INACTIVE&quot;\n",
       "        }\n",
       "      ],\n",
       "      [\n",
       "        {\n",
       "          &quot;action&quot;: 2,\n",
       "          &quot;reward&quot;: 0,\n",
       "          &quot;info&quot;: {},\n",
       "          &quot;observation&quot;: {\n",
       "            &quot;remainingOverageTime&quot;: 2,\n",
       "            &quot;step&quot;: 3,\n",
       "            &quot;board&quot;: [\n",
       "              1,\n",
       "              0,\n",
       "              1,\n",
       "              0,\n",
       "              0,\n",
       "              2,\n",
       "              0,\n",
       "              0,\n",
       "              0\n",
       "            ],\n",
       "            &quot;mark&quot;: 1\n",
       "          },\n",
       "          &quot;status&quot;: &quot;INACTIVE&quot;\n",
       "        },\n",
       "        {\n",
       "          &quot;action&quot;: 0,\n",
       "          &quot;reward&quot;: 0,\n",
       "          &quot;info&quot;: {},\n",
       "          &quot;observation&quot;: {\n",
       "            &quot;remainingOverageTime&quot;: 2,\n",
       "            &quot;mark&quot;: 2\n",
       "          },\n",
       "          &quot;status&quot;: &quot;ACTIVE&quot;\n",
       "        }\n",
       "      ],\n",
       "      [\n",
       "        {\n",
       "          &quot;action&quot;: 0,\n",
       "          &quot;reward&quot;: 0,\n",
       "          &quot;info&quot;: {},\n",
       "          &quot;observation&quot;: {\n",
       "            &quot;remainingOverageTime&quot;: 2,\n",
       "            &quot;step&quot;: 4,\n",
       "            &quot;board&quot;: [\n",
       "              1,\n",
       "              2,\n",
       "              1,\n",
       "              0,\n",
       "              0,\n",
       "              2,\n",
       "              0,\n",
       "              0,\n",
       "              0\n",
       "            ],\n",
       "            &quot;mark&quot;: 1\n",
       "          },\n",
       "          &quot;status&quot;: &quot;ACTIVE&quot;\n",
       "        },\n",
       "        {\n",
       "          &quot;action&quot;: 1,\n",
       "          &quot;reward&quot;: 0,\n",
       "          &quot;info&quot;: {},\n",
       "          &quot;observation&quot;: {\n",
       "            &quot;remainingOverageTime&quot;: 2,\n",
       "            &quot;mark&quot;: 2\n",
       "          },\n",
       "          &quot;status&quot;: &quot;INACTIVE&quot;\n",
       "        }\n",
       "      ],\n",
       "      [\n",
       "        {\n",
       "          &quot;action&quot;: 3,\n",
       "          &quot;reward&quot;: 0,\n",
       "          &quot;info&quot;: {},\n",
       "          &quot;observation&quot;: {\n",
       "            &quot;remainingOverageTime&quot;: 2,\n",
       "            &quot;step&quot;: 5,\n",
       "            &quot;board&quot;: [\n",
       "              1,\n",
       "              2,\n",
       "              1,\n",
       "              1,\n",
       "              0,\n",
       "              2,\n",
       "              0,\n",
       "              0,\n",
       "              0\n",
       "            ],\n",
       "            &quot;mark&quot;: 1\n",
       "          },\n",
       "          &quot;status&quot;: &quot;INACTIVE&quot;\n",
       "        },\n",
       "        {\n",
       "          &quot;action&quot;: 0,\n",
       "          &quot;reward&quot;: 0,\n",
       "          &quot;info&quot;: {},\n",
       "          &quot;observation&quot;: {\n",
       "            &quot;remainingOverageTime&quot;: 2,\n",
       "            &quot;mark&quot;: 2\n",
       "          },\n",
       "          &quot;status&quot;: &quot;ACTIVE&quot;\n",
       "        }\n",
       "      ],\n",
       "      [\n",
       "        {\n",
       "          &quot;action&quot;: 0,\n",
       "          &quot;reward&quot;: 0,\n",
       "          &quot;info&quot;: {},\n",
       "          &quot;observation&quot;: {\n",
       "            &quot;remainingOverageTime&quot;: 2,\n",
       "            &quot;step&quot;: 6,\n",
       "            &quot;board&quot;: [\n",
       "              1,\n",
       "              2,\n",
       "              1,\n",
       "              1,\n",
       "              0,\n",
       "              2,\n",
       "              2,\n",
       "              0,\n",
       "              0\n",
       "            ],\n",
       "            &quot;mark&quot;: 1\n",
       "          },\n",
       "          &quot;status&quot;: &quot;ACTIVE&quot;\n",
       "        },\n",
       "        {\n",
       "          &quot;action&quot;: 6,\n",
       "          &quot;reward&quot;: 0,\n",
       "          &quot;info&quot;: {},\n",
       "          &quot;observation&quot;: {\n",
       "            &quot;remainingOverageTime&quot;: 2,\n",
       "            &quot;mark&quot;: 2\n",
       "          },\n",
       "          &quot;status&quot;: &quot;INACTIVE&quot;\n",
       "        }\n",
       "      ],\n",
       "      [\n",
       "        {\n",
       "          &quot;action&quot;: 7,\n",
       "          &quot;reward&quot;: 0,\n",
       "          &quot;info&quot;: {},\n",
       "          &quot;observation&quot;: {\n",
       "            &quot;remainingOverageTime&quot;: 2,\n",
       "            &quot;step&quot;: 7,\n",
       "            &quot;board&quot;: [\n",
       "              1,\n",
       "              2,\n",
       "              1,\n",
       "              1,\n",
       "              0,\n",
       "              2,\n",
       "              2,\n",
       "              1,\n",
       "              0\n",
       "            ],\n",
       "            &quot;mark&quot;: 1\n",
       "          },\n",
       "          &quot;status&quot;: &quot;INACTIVE&quot;\n",
       "        },\n",
       "        {\n",
       "          &quot;action&quot;: 0,\n",
       "          &quot;reward&quot;: 0,\n",
       "          &quot;info&quot;: {},\n",
       "          &quot;observation&quot;: {\n",
       "            &quot;remainingOverageTime&quot;: 2,\n",
       "            &quot;mark&quot;: 2\n",
       "          },\n",
       "          &quot;status&quot;: &quot;ACTIVE&quot;\n",
       "        }\n",
       "      ],\n",
       "      [\n",
       "        {\n",
       "          &quot;action&quot;: 0,\n",
       "          &quot;reward&quot;: 0,\n",
       "          &quot;info&quot;: {},\n",
       "          &quot;observation&quot;: {\n",
       "            &quot;remainingOverageTime&quot;: 2,\n",
       "            &quot;step&quot;: 8,\n",
       "            &quot;board&quot;: [\n",
       "              1,\n",
       "              2,\n",
       "              1,\n",
       "              1,\n",
       "              2,\n",
       "              2,\n",
       "              2,\n",
       "              1,\n",
       "              0\n",
       "            ],\n",
       "            &quot;mark&quot;: 1\n",
       "          },\n",
       "          &quot;status&quot;: &quot;ACTIVE&quot;\n",
       "        },\n",
       "        {\n",
       "          &quot;action&quot;: 4,\n",
       "          &quot;reward&quot;: 0,\n",
       "          &quot;info&quot;: {},\n",
       "          &quot;observation&quot;: {\n",
       "            &quot;remainingOverageTime&quot;: 2,\n",
       "            &quot;mark&quot;: 2\n",
       "          },\n",
       "          &quot;status&quot;: &quot;INACTIVE&quot;\n",
       "        }\n",
       "      ],\n",
       "      [\n",
       "        {\n",
       "          &quot;action&quot;: 8,\n",
       "          &quot;reward&quot;: 0,\n",
       "          &quot;info&quot;: {},\n",
       "          &quot;observation&quot;: {\n",
       "            &quot;remainingOverageTime&quot;: 2,\n",
       "            &quot;step&quot;: 9,\n",
       "            &quot;board&quot;: [\n",
       "              1,\n",
       "              2,\n",
       "              1,\n",
       "              1,\n",
       "              2,\n",
       "              2,\n",
       "              2,\n",
       "              1,\n",
       "              1\n",
       "            ],\n",
       "            &quot;mark&quot;: 1\n",
       "          },\n",
       "          &quot;status&quot;: &quot;DONE&quot;\n",
       "        },\n",
       "        {\n",
       "          &quot;action&quot;: 0,\n",
       "          &quot;reward&quot;: 0,\n",
       "          &quot;info&quot;: {},\n",
       "          &quot;observation&quot;: {\n",
       "            &quot;remainingOverageTime&quot;: 2,\n",
       "            &quot;mark&quot;: 2\n",
       "          },\n",
       "          &quot;status&quot;: &quot;DONE&quot;\n",
       "        }\n",
       "      ]\n",
       "    ],\n",
       "    &quot;rewards&quot;: [\n",
       "      0,\n",
       "      0\n",
       "    ],\n",
       "    &quot;statuses&quot;: [\n",
       "      &quot;DONE&quot;,\n",
       "      &quot;DONE&quot;\n",
       "    ],\n",
       "    &quot;schema_version&quot;: 1,\n",
       "    &quot;info&quot;: {}\n",
       "  },\n",
       "  &quot;logs&quot;: [\n",
       "    [],\n",
       "    [],\n",
       "    [\n",
       "      {\n",
       "        &quot;duration&quot;: 8.574066,\n",
       "        &quot;stdout&quot;: &quot;&quot;,\n",
       "        &quot;stderr&quot;: &quot;&quot;\n",
       "      },\n",
       "      {}\n",
       "    ],\n",
       "    [\n",
       "      {},\n",
       "      {\n",
       "        &quot;duration&quot;: 5e-05,\n",
       "        &quot;stdout&quot;: &quot;&quot;,\n",
       "        &quot;stderr&quot;: &quot;&quot;\n",
       "      }\n",
       "    ],\n",
       "    [\n",
       "      {\n",
       "        &quot;duration&quot;: 0.099802,\n",
       "        &quot;stdout&quot;: &quot;&quot;,\n",
       "        &quot;stderr&quot;: &quot;&quot;\n",
       "      },\n",
       "      {}\n",
       "    ],\n",
       "    [\n",
       "      {},\n",
       "      {\n",
       "        &quot;duration&quot;: 2.6e-05,\n",
       "        &quot;stdout&quot;: &quot;&quot;,\n",
       "        &quot;stderr&quot;: &quot;&quot;\n",
       "      }\n",
       "    ],\n",
       "    [\n",
       "      {\n",
       "        &quot;duration&quot;: 0.003582,\n",
       "        &quot;stdout&quot;: &quot;&quot;,\n",
       "        &quot;stderr&quot;: &quot;&quot;\n",
       "      },\n",
       "      {}\n",
       "    ],\n",
       "    [\n",
       "      {},\n",
       "      {\n",
       "        &quot;duration&quot;: 2.9e-05,\n",
       "        &quot;stdout&quot;: &quot;&quot;,\n",
       "        &quot;stderr&quot;: &quot;&quot;\n",
       "      }\n",
       "    ],\n",
       "    [\n",
       "      {\n",
       "        &quot;duration&quot;: 0.000252,\n",
       "        &quot;stdout&quot;: &quot;&quot;,\n",
       "        &quot;stderr&quot;: &quot;&quot;\n",
       "      },\n",
       "      {}\n",
       "    ],\n",
       "    [\n",
       "      {},\n",
       "      {\n",
       "        &quot;duration&quot;: 4.8e-05,\n",
       "        &quot;stdout&quot;: &quot;&quot;,\n",
       "        &quot;stderr&quot;: &quot;&quot;\n",
       "      }\n",
       "    ],\n",
       "    [\n",
       "      {\n",
       "        &quot;duration&quot;: 4.2e-05,\n",
       "        &quot;stdout&quot;: &quot;&quot;,\n",
       "        &quot;stderr&quot;: &quot;&quot;\n",
       "      },\n",
       "      {}\n",
       "    ]\n",
       "  ],\n",
       "  &quot;mode&quot;: &quot;ipython&quot;,\n",
       "  &quot;width&quot;: 200,\n",
       "  &quot;height&quot;: 200\n",
       "};\n",
       "\n",
       "\n",
       "window.kaggle.renderer = // Copyright 2020 Kaggle Inc\n",
       "//\n",
       "// Licensed under the Apache License, Version 2.0 (the &quot;License&quot;);\n",
       "// you may not use this file except in compliance with the License.\n",
       "// You may obtain a copy of the License at\n",
       "//\n",
       "//      http://www.apache.org/licenses/LICENSE-2.0\n",
       "//\n",
       "// Unless required by applicable law or agreed to in writing, software\n",
       "// distributed under the License is distributed on an &quot;AS IS&quot; BASIS,\n",
       "// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
       "// See the License for the specific language governing permissions and\n",
       "// limitations under the License.\n",
       "\n",
       "async function renderer(context) {\n",
       "  const {\n",
       "    act,\n",
       "    agents,\n",
       "    environment,\n",
       "    frame,\n",
       "    height = 400,\n",
       "    interactive,\n",
       "    isInteractive,\n",
       "    parent,\n",
       "    step,\n",
       "    update,\n",
       "    width = 400,\n",
       "  } = context;\n",
       "\n",
       "  // Common Dimensions.\n",
       "  const canvasSize = Math.min(height, width);\n",
       "  const unit = 8;\n",
       "  const offset = canvasSize > 400 ? canvasSize * 0.1 : unit / 2;\n",
       "  const cellSize = (canvasSize - offset * 2) / 3;\n",
       "\n",
       "  // Canvas Setup.\n",
       "  let canvas = parent.querySelector(&quot;canvas&quot;);\n",
       "  if (!canvas) {\n",
       "    canvas = document.createElement(&quot;canvas&quot;);\n",
       "    parent.appendChild(canvas);\n",
       "\n",
       "    if (interactive) {\n",
       "      canvas.addEventListener(&quot;click&quot;, evt => {\n",
       "        if (!isInteractive()) return;\n",
       "        const rect = evt.target.getBoundingClientRect();\n",
       "        const x = evt.clientX - rect.left - offset;\n",
       "        const y = evt.clientY - rect.top - offset;\n",
       "        act(Math.floor(x / cellSize) + Math.floor(y / cellSize) * 3);\n",
       "      });\n",
       "    }\n",
       "  }\n",
       "  canvas.style.cursor = isInteractive() ? &quot;pointer&quot; : &quot;default&quot;;\n",
       "\n",
       "  // Canvas setup and reset.\n",
       "  let c = canvas.getContext(&quot;2d&quot;);\n",
       "  canvas.width = canvasSize;\n",
       "  canvas.height = canvasSize;\n",
       "  c.clearRect(0, 0, canvas.width, canvas.height);\n",
       "\n",
       "  const drawStyle = ({\n",
       "    lineWidth = 1,\n",
       "    lineCap,\n",
       "    strokeStyle = &quot;#FFF&quot;,\n",
       "    shadow,\n",
       "  }) => {\n",
       "    c.lineWidth = lineWidth;\n",
       "    c.strokeStyle = strokeStyle;\n",
       "    if (lineCap) c.lineCap = lineCap;\n",
       "    if (shadow) {\n",
       "      c.shadowOffsetX = shadow.offsetX || 0;\n",
       "      c.shadowOffsetY = shadow.offsetY || 0;\n",
       "      c.shadowColor = shadow.color || strokeStyle;\n",
       "      c.shadowBlur = shadow.blur || 0;\n",
       "    }\n",
       "  };\n",
       "\n",
       "  const drawLine = ({ x1, y1, x2, y2, style }) => {\n",
       "    c.beginPath();\n",
       "    drawStyle(style || {});\n",
       "    c.moveTo((x1 || 0) + offset, (y1 || 0) + offset);\n",
       "    c.lineTo((x2 || x1) + offset, (y2 || y1) + offset);\n",
       "    c.stroke();\n",
       "  };\n",
       "\n",
       "  const drawArc = ({ x, y, radius, sAngle, eAngle, style }) => {\n",
       "    drawStyle(style || {});\n",
       "    c.beginPath();\n",
       "    c.arc(x, y, radius, sAngle, eAngle);\n",
       "    c.stroke();\n",
       "  };\n",
       "\n",
       "  // Draw the Grid.\n",
       "  const gridFrame = step === 0 ? frame : 1;\n",
       "  const drawGridLine = ({\n",
       "    x1s = 0,\n",
       "    y1s = 0,\n",
       "    x2s,\n",
       "    y2s,\n",
       "    x1o = 0,\n",
       "    x2o = 0,\n",
       "    y1o = 0,\n",
       "    y2o = 0,\n",
       "  }) =>\n",
       "    drawLine({\n",
       "      x1: x1s * cellSize + x1o * unit,\n",
       "      x2: (x2s || x1s) * cellSize + x2o * unit,\n",
       "      y1: y1s * cellSize + y1o * unit,\n",
       "      y2: (y2s || y1s) * cellSize + y2o * unit,\n",
       "      style: { strokeStyle: &quot;#046BBF&quot; },\n",
       "    });\n",
       "\n",
       "  // Vertical.\n",
       "  drawGridLine({ x1s: 1, y1s: 0, y2s: gridFrame, y2o: -1 });\n",
       "  drawGridLine({ x1s: 2, y1s: 0, y2s: gridFrame, y2o: -1 });\n",
       "  drawGridLine({ x1s: 1, y1s: 1, y2s: 1 + gridFrame, y1o: 1, y2o: -1 });\n",
       "  drawGridLine({ x1s: 2, y1s: 1, y2s: 1 + gridFrame, y1o: 1, y2o: -1 });\n",
       "  drawGridLine({ x1s: 1, y1s: 2, y2s: 2 + gridFrame, y1o: 1 });\n",
       "  drawGridLine({ x1s: 2, y1s: 2, y2s: 2 + gridFrame, y1o: 1 });\n",
       "\n",
       "  // Horizontal.\n",
       "  drawGridLine({ x1s: 0, y1s: 1, x2s: gridFrame, x2o: -1 });\n",
       "  drawGridLine({ x1s: 1, y1s: 1, x2s: 1 + gridFrame, x1o: 1, x2o: -1 });\n",
       "  drawGridLine({ x1s: 2, y1s: 1, x2s: 2 + gridFrame, x1o: 1 });\n",
       "  drawGridLine({ x1s: 0, y1s: 2, x2s: gridFrame, x2o: -1 });\n",
       "  drawGridLine({ x1s: 1, y1s: 2, x2s: 1 + gridFrame, x1o: 1, x2o: -1 });\n",
       "  drawGridLine({ x1s: 2, y1s: 2, x2s: 2 + gridFrame, x1o: 1 });\n",
       "\n",
       "  // Draw the Pieces.\n",
       "  const drawX = (cell, cellFrame) => {\n",
       "    const part = cellSize / 4;\n",
       "    const gap = Math.min(Math.sqrt((unit * unit) / 2), canvasSize / 50);\n",
       "    const row = Math.floor(cell / 3);\n",
       "    const col = cell % 3;\n",
       "\n",
       "    const drawXLine = ({ x1, y1, x2, y2 }) =>\n",
       "      drawLine({\n",
       "        x1: col * cellSize + x1,\n",
       "        y1: row * cellSize + y1,\n",
       "        x2: col * cellSize + x2,\n",
       "        y2: row * cellSize + y2,\n",
       "        style: {\n",
       "          strokeStyle: &quot;#00FFFF&quot;,\n",
       "          lineWidth: 2,\n",
       "          lineCap: &quot;round&quot;,\n",
       "          shadow: { blur: 8 },\n",
       "        },\n",
       "      });\n",
       "\n",
       "    drawXLine({\n",
       "      x1: part,\n",
       "      y1: part,\n",
       "      x2: part + part * 2 * cellFrame,\n",
       "      y2: part + part * 2 * cellFrame,\n",
       "    });\n",
       "    if (Math.round(cellFrame) === 1) {\n",
       "      drawXLine({\n",
       "        x1: part,\n",
       "        y1: part * 3,\n",
       "        x2: part * 2 - gap,\n",
       "        y2: part * 2 + gap,\n",
       "      });\n",
       "      drawXLine({\n",
       "        x1: part * 2 + gap,\n",
       "        y1: part * 2 - gap,\n",
       "        x2: part * 3,\n",
       "        y2: part,\n",
       "      });\n",
       "    }\n",
       "  };\n",
       "  const drawO = (cell, cellFrame) => {\n",
       "    const row = Math.floor(cell / 3);\n",
       "    const col = cell % 3;\n",
       "    const radius = cellSize / 4 + 1; // +1 is for optical illusion.\n",
       "    const gap =\n",
       "      (Math.acos((2 * (radius ^ 2) - (unit ^ 2)) / (2 * radius * radius)) /\n",
       "        180) *\n",
       "      Math.PI *\n",
       "      unit;\n",
       "    const x = cellSize * col + cellSize / 2 + offset;\n",
       "    const y = cellSize * row + cellSize / 2 + offset;\n",
       "\n",
       "    const drawOArc = (sAngle, eAngle) =>\n",
       "      drawArc({\n",
       "        x,\n",
       "        y,\n",
       "        radius,\n",
       "        sAngle,\n",
       "        eAngle,\n",
       "        style: {\n",
       "          lineWidth: 2,\n",
       "          strokeStyle: &quot;#FFF&quot;,\n",
       "          shadow: { blur: 8 },\n",
       "        },\n",
       "      });\n",
       "\n",
       "    drawOArc(\n",
       "      -Math.PI / 2 + gap,\n",
       "      -Math.PI / 2 + gap + (Math.PI - gap * 2) * cellFrame\n",
       "    );\n",
       "    drawOArc(\n",
       "      Math.PI / 2 + gap,\n",
       "      Math.PI / 2 + gap + (Math.PI - gap * 2) * cellFrame\n",
       "    );\n",
       "  };\n",
       "\n",
       "  const board = environment.steps[step][0].observation.board;\n",
       "\n",
       "  board.forEach((value, cell) => {\n",
       "    const cellFrame =\n",
       "      step <= 1 ||\n",
       "      environment.steps[step - 1][0].observation.board[cell] !== value\n",
       "        ? frame\n",
       "        : 1;\n",
       "    if (value === 1) drawX(cell, cellFrame);\n",
       "    if (value === 2) drawO(cell, cellFrame);\n",
       "  });\n",
       "\n",
       "  // Draw the winning line.\n",
       "  // [cell1, cell2, cell3, x1, y1, x2, y2]\n",
       "  const checks = [\n",
       "    [0, 1, 2, 1 / 19, 1 / 6, 18 / 19, 1 / 6],\n",
       "    [3, 4, 5, 1 / 19, 1 / 2, 18 / 19, 1 / 2],\n",
       "    [6, 7, 8, 1 / 19, 5 / 6, 18 / 19, 5 / 6],\n",
       "    [0, 3, 6, 1 / 6, 1 / 19, 1 / 6, 18 / 19],\n",
       "    [1, 4, 7, 1 / 2, 1 / 19, 1 / 2, 18 / 19],\n",
       "    [2, 5, 8, 5 / 6, 1 / 19, 5 / 6, 18 / 19],\n",
       "    [0, 4, 8, 1 / 19, 1 / 19, 18 / 19, 18 / 19],\n",
       "    [2, 4, 6, 18 / 19, 1 / 19, 1 / 19, 18 / 19],\n",
       "  ];\n",
       "  for (const check of checks) {\n",
       "    if (\n",
       "      board[check[0]] !== 0 &&\n",
       "      board[check[0]] === board[check[1]] &&\n",
       "      board[check[0]] === board[check[2]]\n",
       "    ) {\n",
       "      const x1 = check[3] * (cellSize * 3);\n",
       "      const y1 = check[4] * (cellSize * 3);\n",
       "      const winFrame = frame < 0.5 ? 0 : (frame - 0.5) / 0.5;\n",
       "      if (winFrame > 0) {\n",
       "        drawLine({\n",
       "          x1,\n",
       "          y1,\n",
       "          x2: x1 + (check[5] * (cellSize * 3) - x1) * winFrame,\n",
       "          y2: y1 + (check[6] * (cellSize * 3) - y1) * winFrame,\n",
       "          style: {\n",
       "            strokeStyle: &quot;#FFF&quot;,\n",
       "            lineWidth: 3 * winFrame,\n",
       "            shadow: { blur: 8 * winFrame },\n",
       "          },\n",
       "        });\n",
       "      }\n",
       "      break;\n",
       "    }\n",
       "  }\n",
       "\n",
       "  // Upgrade the legend.\n",
       "  if (agents.length && (!agents[0].color || !agents[0].image)) {\n",
       "    const getPieceImage = drawFn => {\n",
       "      const pieceCanvas = document.createElement(&quot;canvas&quot;);\n",
       "      parent.appendChild(pieceCanvas);\n",
       "      pieceCanvas.style.marginLeft = &quot;10000px&quot;;\n",
       "      pieceCanvas.width = cellSize + offset * 2;\n",
       "      pieceCanvas.height = cellSize + offset * 2;\n",
       "      c = pieceCanvas.getContext(&quot;2d&quot;);\n",
       "      drawFn(0, 1);\n",
       "      const dataUrl = pieceCanvas.toDataURL();\n",
       "      parent.removeChild(pieceCanvas);\n",
       "      return dataUrl;\n",
       "    };\n",
       "\n",
       "    agents.forEach(agent => {\n",
       "      agent.color = agent.index === 0 ? &quot;#0FF&quot; : &quot;#FFF&quot;;\n",
       "      agent.image = getPieceImage(agent.index === 0 ? drawX : drawO);\n",
       "    });\n",
       "    update({ agents });\n",
       "  }\n",
       "};\n",
       "\n",
       "\n",
       "    \n",
       "    </script>\n",
       "    <script>\n",
       "      const h = htm.bind(preact.h);\n",
       "      const { useContext, useEffect, useRef, useState } = preactHooks;\n",
       "      const styled = window.styled.default;\n",
       "\n",
       "      const Context = preact.createContext({});\n",
       "\n",
       "      const Loading = styled.div`\n",
       "        animation: rotate360 1.1s infinite linear;\n",
       "        border: 8px solid rgba(255, 255, 255, 0.2);\n",
       "        border-left-color: #0cb1ed;\n",
       "        border-radius: 50%;\n",
       "        height: 40px;\n",
       "        position: relative;\n",
       "        transform: translateZ(0);\n",
       "        width: 40px;\n",
       "\n",
       "        @keyframes rotate360 {\n",
       "          0% {\n",
       "            transform: rotate(0deg);\n",
       "          }\n",
       "          100% {\n",
       "            transform: rotate(360deg);\n",
       "          }\n",
       "        }\n",
       "      `;\n",
       "\n",
       "      const Logo = styled(\n",
       "        (props) => h`\n",
       "        <a href=&quot;https://kaggle.com&quot; target=&quot;_blank&quot; className=${props.className}>\n",
       "          <svg width=&quot;62px&quot; height=&quot;20px&quot; viewBox=&quot;0 0 62 24&quot; version=&quot;1.1&quot; xmlns=&quot;http://www.w3.org/2000/svg&quot;>\n",
       "            <g fill=&quot;#1EBEFF&quot; fill-rule=&quot;nonzero&quot;>\n",
       "              <path d=&quot;M10.2,17.8c0,0.1-0.1,0.1-0.2,0.1H7.7c-0.1,0-0.3-0.1-0.4-0.2l-3.8-4.9l-1.1,1v3.8 c0,0.2-0.1,0.3-0.3,0.3H0.3c-0.2,0-0.3-0.1-0.3-0.3V0.3C0.1,0.1,0.2,0,0.3,0h1.8c0.2,0,0.3,0.1,0.3,0.3V11L7,6.3 c0.1-0.1,0.2-0.2,0.4-0.2h2.4c0.1,0,0.2,0,0.2,0.1c0,0.1,0,0.2,0,0.2l-4.9,4.7l5.1,6.3C10.2,17.6,10.2,17.7,10.2,17.8z&quot;/>\n",
       "              <path d=&quot;M19.6,17.9h-1.8c-0.2,0-0.3-0.1-0.3-0.3v-0.4c-0.8,0.6-1.8,0.9-3,0.9c-1.1,0-2-0.3-2.8-1 c-0.8-0.7-1.2-1.6-1.2-2.7c0-1.7,1.1-2.9,3.2-3.5c0.8-0.2,2.1-0.5,3.8-0.6c0.1-0.6-0.1-1.2-0.5-1.7c-0.4-0.5-1-0.7-1.7-0.7 c-1,0-2,0.4-3,1C12.2,9.1,12.1,9.1,12,9l-0.9-1.3C11,7.5,11,7.4,11.1,7.3c1.3-0.9,2.7-1.4,4.2-1.4c1.1,0,2.1,0.3,2.8,0.8 c1.1,0.8,1.7,2,1.7,3.7v7.3C19.9,17.8,19.8,17.9,19.6,17.9z M17.5,12.4c-1.7,0.2-2.9,0.4-3.5,0.7c-0.9,0.4-1.2,0.9-1.1,1.6 c0.1,0.4,0.2,0.7,0.6,0.9c0.3,0.2,0.7,0.4,1.1,0.4c1.2,0.1,2.2-0.2,2.9-1V12.4z&quot;/>\n",
       "              <path d=&quot;M30.6,22.5c-0.9,1-2.3,1.5-4,1.5c-1,0-2-0.3-2.9-0.8c-0.2-0.1-0.4-0.3-0.7-0.5 c-0.3-0.2-0.6-0.5-0.9-0.7c-0.1-0.1-0.1-0.2,0-0.4l1.2-1.2c0.1-0.1,0.1-0.1,0.2-0.1c0.1,0,0.1,0,0.2,0.1c1,1,1.9,1.5,2.8,1.5 c2.1,0,3.2-1.1,3.2-3.3v-1.4c-0.8,0.7-1.9,1-3.3,1c-1.7,0-3-0.6-4-1.9c-0.8-1.1-1.3-2.5-1.3-4.2c0-1.6,0.4-3,1.2-4.1 c0.9-1.3,2.3-2,4-2c1.3,0,2.4,0.3,3.3,1V6.4c0-0.2,0.1-0.3,0.3-0.3h1.8c0.2,0,0.3,0.1,0.3,0.3v11.7C32,20,31.5,21.5,30.6,22.5z M29.7,9.9c-0.4-1.1-1.4-1.7-3-1.7c-2,0-3.1,1.3-3.1,3.8c0,1.4,0.3,2.4,1,3.1c0.5,0.5,1.2,0.8,2,0.8c1.6,0,2.7-0.6,3.1-1.7V9.9z&quot;/>\n",
       "              <path d=&quot;M42.9,22.5c-0.9,1-2.3,1.5-4,1.5c-1,0-2-0.3-2.9-0.8c-0.2-0.1-0.4-0.3-0.7-0.5 c-0.3-0.2-0.6-0.5-0.9-0.7c-0.1-0.1-0.1-0.2,0-0.4l1.2-1.2c0.1-0.1,0.1-0.1,0.2-0.1c0.1,0,0.1,0,0.2,0.1c1,1,1.9,1.5,2.8,1.5 c2.1,0,3.2-1.1,3.2-3.3v-1.4c-0.8,0.7-1.9,1-3.3,1c-1.7,0-3-0.6-4-1.9c-0.8-1.1-1.3-2.5-1.3-4.2c0-1.6,0.4-3,1.2-4.1 c0.9-1.3,2.3-2,4-2c1.3,0,2.4,0.3,3.3,1V6.4c0-0.2,0.1-0.3,0.3-0.3H44c0.2,0,0.3,0.1,0.3,0.3v11.7C44.3,20,43.8,21.5,42.9,22.5z M42,9.9c-0.4-1.1-1.4-1.7-3-1.7c-2,0-3.1,1.3-3.1,3.8c0,1.4,0.3,2.4,1,3.1c0.5,0.5,1.2,0.8,2,0.8c1.6,0,2.7-0.6,3.1-1.7L42,9.9 L42,9.9z&quot;/>\n",
       "              <path d=&quot;M48.3,17.9h-1.8c-0.2,0-0.3-0.1-0.3-0.3V0.3c0-0.2,0.1-0.3,0.3-0.3h1.8c0.2,0,0.3,0.1,0.3,0.3 v17.3C48.5,17.8,48.5,17.9,48.3,17.9z&quot;/>\n",
       "              <path d=&quot;M61.4,12.6c0,0.2-0.1,0.3-0.3,0.3h-8.5c0.1,0.9,0.5,1.6,1.1,2.2c0.7,0.6,1.6,0.9,2.7,0.9 c1,0,1.8-0.3,2.6-0.8c0.2-0.1,0.3-0.1,0.4,0l1.2,1.3c0.1,0.1,0.1,0.3,0,0.4c-1.3,0.9-2.7,1.4-4.4,1.4c-1.8,0-3.3-0.6-4.4-1.8 c-1.1-1.2-1.7-2.7-1.7-4.5c0-1.7,0.6-3.2,1.7-4.4c1-1.1,2.4-1.6,4.1-1.6c1.6,0,2.9,0.6,4,1.7c1.1,1.2,1.6,2.6,1.5,4.4L61.4,12.6 z M58,8.7c-0.6-0.5-1.3-0.8-2.1-0.8c-0.8,0-1.5,0.3-2.1,0.8c-0.6,0.5-1,1.2-1.1,2H59C59,9.9,58.6,9.3,58,8.7z&quot;/>\n",
       "            </g>\n",
       "          </svg>\n",
       "        </a>\n",
       "      `\n",
       "      )`\n",
       "        display: inline-flex;\n",
       "      `;\n",
       "\n",
       "      const Header = styled((props) => {\n",
       "        const { environment } = useContext(Context);\n",
       "\n",
       "        return h`<div className=${props.className} >\n",
       "          <${Logo} />\n",
       "          <span><b>Left / Right Arrow:</b> Increase / Decrease Step</span><span><b>0-9 Row Keys:</b> Playback Speed</span><span><b>Space:</b> Pause / Play</span>\n",
       "          ${environment.title}\n",
       "        </div>`;\n",
       "      })`\n",
       "        align-items: center;\n",
       "        border-bottom: 4px solid #212121;\n",
       "        box-sizing: border-box;\n",
       "        color: #fff;\n",
       "        display: flex;\n",
       "        flex: 0 0 36px;\n",
       "        font-size: 14px;\n",
       "        justify-content: space-between;\n",
       "        padding: 0 8px;\n",
       "        width: 100%;\n",
       "      `;\n",
       "\n",
       "      const Renderer = styled((props) => {\n",
       "        const context = useContext(Context);\n",
       "        const { animate, debug, playing, renderer, speed } = context;\n",
       "        const ref = preact.createRef();\n",
       "\n",
       "        useEffect(async () => {\n",
       "          if (!ref.current) return;\n",
       "\n",
       "          const renderFrame = async (start, step, lastFrame) => {\n",
       "            if (step !== context.step) return;\n",
       "            if (lastFrame === 1) {\n",
       "              if (!animate) return;\n",
       "              start = Date.now();\n",
       "            }\n",
       "            const frame =\n",
       "              playing || animate\n",
       "                ? Math.min((Date.now() - start) / speed, 1)\n",
       "                : 1;\n",
       "            try {\n",
       "              if (debug) console.time(&quot;render&quot;);\n",
       "              await renderer({\n",
       "                ...context,\n",
       "                frame,\n",
       "                height: ref.current.clientHeight,\n",
       "                hooks: preactHooks,\n",
       "                parent: ref.current,\n",
       "                preact,\n",
       "                styled,\n",
       "                width: ref.current.clientWidth,\n",
       "              });\n",
       "            } catch (error) {\n",
       "              if (debug) console.error(error);\n",
       "              console.log({ ...context, frame, error });\n",
       "            } finally {\n",
       "              if (debug) console.timeEnd(&quot;render&quot;);\n",
       "            }\n",
       "            window.requestAnimationFrame(() => renderFrame(start, step, frame));\n",
       "          };\n",
       "\n",
       "          await renderFrame(Date.now(), context.step);\n",
       "        }, [ref.current, context.step, context.renderer]);\n",
       "\n",
       "        return h`<div className=${props.className} ref=${ref} />`;\n",
       "      })`\n",
       "        align-items: center;\n",
       "        box-sizing: border-box;\n",
       "        display: flex;\n",
       "        height: 100%;\n",
       "        left: 0;\n",
       "        justify-content: center;\n",
       "        position: absolute;\n",
       "        top: 0;\n",
       "        width: 100%;\n",
       "      `;\n",
       "\n",
       "      const Processing = styled((props) => {\n",
       "        const { processing } = useContext(Context);\n",
       "        const text = processing === true ? &quot;Processing...&quot; : processing;\n",
       "        return h`<div className=${props.className}>${text}</div>`;\n",
       "      })`\n",
       "        bottom: 0;\n",
       "        color: #fff;\n",
       "        font-size: 12px;\n",
       "        left: 0;\n",
       "        line-height: 24px;\n",
       "        position: absolute;\n",
       "        text-align: center;\n",
       "        width: 100%;\n",
       "      `;\n",
       "\n",
       "      const Viewer = styled((props) => {\n",
       "        const { processing } = useContext(Context);\n",
       "        return h`<div className=${props.className}>\n",
       "          <${Renderer} />\n",
       "          ${processing && h`<${Processing} />`}\n",
       "        </div>`;\n",
       "      })`\n",
       "        background-color: #000b2a;\n",
       "        background-image: radial-gradient(\n",
       "          circle closest-side,\n",
       "          #000b49,\n",
       "          #000b2a\n",
       "        );\n",
       "        display: flex;\n",
       "        flex: 1;\n",
       "        overflow: hidden;\n",
       "        position: relative;\n",
       "        width: 100%;\n",
       "      `;\n",
       "\n",
       "      // Partitions the elements of arr into subarrays of max length num.\n",
       "      const groupIntoSets = (arr, num) => {\n",
       "        const sets = [];\n",
       "        arr.forEach(a => {\n",
       "          if (sets.length === 0 || sets[sets.length - 1].length === num) {\n",
       "            sets.push([]);\n",
       "          }\n",
       "          sets[sets.length - 1].push(a);\n",
       "        });\n",
       "        return sets;\n",
       "      }\n",
       "\n",
       "      // Expects `width` input prop to set proper max-width for agent name span.\n",
       "      const Legend = styled((props) => {\n",
       "        const { agents, legend } = useContext(Context);\n",
       "\n",
       "        const agentPairs = groupIntoSets(agents.sort((a, b) => a.index - b.index), 2);\n",
       "\n",
       "        return h`<div className=${props.className}>\n",
       "          ${agentPairs.map(agentList =>\n",
       "            h`<ul>\n",
       "                ${agentList.map(a =>\n",
       "                  h`<li key=${a.id} title=&quot;id: ${a.id}&quot; style=&quot;color:${a.color || &quot;#FFF&quot;}&quot;>\n",
       "                      ${a.image && h`<img src=${a.image} />`}\n",
       "                      <span>${a.name}</span>\n",
       "                    </li>`\n",
       "                )}\n",
       "              </ul>`)}\n",
       "        </div>`;\n",
       "      })`\n",
       "        background-color: #000b2a;\n",
       "        font-family: sans-serif;\n",
       "        font-size: 14px;\n",
       "        height: 48px;\n",
       "        width: 100%;\n",
       "\n",
       "        ul {\n",
       "          align-items: center;\n",
       "          display: flex;\n",
       "          flex-direction: row;\n",
       "          justify-content: center;\n",
       "        }\n",
       "\n",
       "        li {\n",
       "          align-items: center;\n",
       "          display: inline-flex;\n",
       "          transition: color 1s;\n",
       "        }\n",
       "\n",
       "        span {\n",
       "          max-width: ${p => (p.width || 400) * 0.5 - 36}px;\n",
       "          overflow: hidden;\n",
       "          text-overflow: ellipsis;\n",
       "          white-space: nowrap;\n",
       "        }\n",
       "\n",
       "        img {\n",
       "          height: 24px;\n",
       "          margin-left: 4px;\n",
       "          margin-right: 4px;\n",
       "          width: 24px;\n",
       "        }\n",
       "      `;\n",
       "\n",
       "      const StepInput = styled.input.attrs({\n",
       "        type: &quot;range&quot;,\n",
       "      })`\n",
       "        appearance: none;\n",
       "        background: rgba(255, 255, 255, 0.15);\n",
       "        border-radius: 2px;\n",
       "        display: block;\n",
       "        flex: 1;\n",
       "        height: 4px;\n",
       "        opacity: 0.8;\n",
       "        outline: none;\n",
       "        transition: opacity 0.2s;\n",
       "        width: 100%;\n",
       "\n",
       "        &:hover {\n",
       "          opacity: 1;\n",
       "        }\n",
       "\n",
       "        &::-webkit-slider-thumb {\n",
       "          appearance: none;\n",
       "          background: #1ebeff;\n",
       "          border-radius: 100%;\n",
       "          cursor: pointer;\n",
       "          height: 12px;\n",
       "          margin: 0;\n",
       "          position: relative;\n",
       "          width: 12px;\n",
       "\n",
       "          &::after {\n",
       "            content: &quot;&quot;;\n",
       "            position: absolute;\n",
       "            top: 0px;\n",
       "            left: 0px;\n",
       "            width: 200px;\n",
       "            height: 8px;\n",
       "            background: green;\n",
       "          }\n",
       "        }\n",
       "      `;\n",
       "\n",
       "      const PlayButton = styled.button`\n",
       "        align-items: center;\n",
       "        background: none;\n",
       "        border: none;\n",
       "        color: white;\n",
       "        cursor: pointer;\n",
       "        display: flex;\n",
       "        flex: 0 0 56px;\n",
       "        font-size: 20px;\n",
       "        height: 40px;\n",
       "        justify-content: center;\n",
       "        opacity: 0.8;\n",
       "        outline: none;\n",
       "        transition: opacity 0.2s;\n",
       "\n",
       "        &:hover {\n",
       "          opacity: 1;\n",
       "        }\n",
       "      `;\n",
       "\n",
       "      const StepCount = styled.span`\n",
       "        align-items: center;\n",
       "        color: white;\n",
       "        display: flex;\n",
       "        font-size: 14px;\n",
       "        justify-content: center;\n",
       "        opacity: 0.8;\n",
       "        padding: 0 16px;\n",
       "        pointer-events: none;\n",
       "      `;\n",
       "\n",
       "      const Controls = styled((props) => {\n",
       "        const { environment, pause, play, playing, setStep, step } = useContext(\n",
       "          Context\n",
       "        );\n",
       "        const value = step + 1;\n",
       "        const onClick = () => (playing ? pause() : play());\n",
       "        const onInput = (e) => {\n",
       "          pause();\n",
       "          setStep(parseInt(e.target.value) - 1);\n",
       "        };\n",
       "\n",
       "        return h`\n",
       "          <div className=${props.className}>\n",
       "            <${PlayButton} onClick=${onClick}><svg xmlns=&quot;http://www.w3.org/2000/svg&quot; width=&quot;24px&quot; height=&quot;24px&quot; viewBox=&quot;0 0 24 24&quot; fill=&quot;#FFFFFF&quot;>${\n",
       "          playing\n",
       "            ? h`<path d=&quot;M6 19h4V5H6v14zm8-14v14h4V5h-4z&quot;/><path d=&quot;M0 0h24v24H0z&quot; fill=&quot;none&quot;/>`\n",
       "            : h`<path d=&quot;M8 5v14l11-7z&quot;/><path d=&quot;M0 0h24v24H0z&quot; fill=&quot;none&quot;/>`\n",
       "        }</svg><//>\n",
       "            <${StepInput} min=&quot;1&quot; max=${\n",
       "          environment.steps.length\n",
       "        } value=&quot;${value}&quot; onInput=${onInput} />\n",
       "            <${StepCount}>${value} / ${environment.steps.length}<//>\n",
       "          </div>\n",
       "        `;\n",
       "      })`\n",
       "        align-items: center;\n",
       "        border-top: 4px solid #212121;\n",
       "        display: flex;\n",
       "        flex: 0 0 44px;\n",
       "        width: 100%;\n",
       "      `;\n",
       "\n",
       "      const Info = styled((props) => {\n",
       "        const {\n",
       "          environment,\n",
       "          playing,\n",
       "          step,\n",
       "          speed,\n",
       "          animate,\n",
       "          header,\n",
       "          controls,\n",
       "          settings,\n",
       "        } = useContext(Context);\n",
       "\n",
       "        return h`\n",
       "          <div className=${props.className}>\n",
       "            info:\n",
       "            step(${step}),\n",
       "            playing(${playing ? &quot;T&quot; : &quot;F&quot;}),\n",
       "            speed(${speed}),\n",
       "            animate(${animate ? &quot;T&quot; : &quot;F&quot;})\n",
       "          </div>`;\n",
       "      })`\n",
       "        color: #888;\n",
       "        font-family: monospace;\n",
       "        font-size: 12px;\n",
       "      `;\n",
       "\n",
       "      const Settings = styled((props) => {\n",
       "        const { environment, pause, play, playing, setStep, step } = useContext(\n",
       "          Context\n",
       "        );\n",
       "\n",
       "        return h`\n",
       "          <div className=${props.className}>\n",
       "            <${Info} />\n",
       "          </div>\n",
       "        `;\n",
       "      })`\n",
       "        background: #fff;\n",
       "        border-top: 4px solid #212121;\n",
       "        box-sizing: border-box;\n",
       "        padding: 20px;\n",
       "        width: 100%;\n",
       "\n",
       "        h1 {\n",
       "          font-size: 20px;\n",
       "        }\n",
       "      `;\n",
       "\n",
       "      const Player = styled((props) => {\n",
       "        const context = useContext(Context);\n",
       "        const { agents, controls, header, legend, loading, settings, width } = context;\n",
       "        return h`\n",
       "          <div className=${props.className}>\n",
       "            ${loading && h`<${Loading} />`}\n",
       "            ${!loading && header && h`<${Header} />`}\n",
       "            ${!loading && h`<${Viewer} />`}\n",
       "            ${!loading && legend && h`<${Legend} width=${width}/>`}\n",
       "            ${!loading && controls && h`<${Controls} />`}\n",
       "            ${!loading && settings && h`<${Settings} />`}\n",
       "          </div>`;\n",
       "      })`\n",
       "        align-items: center;\n",
       "        background: #212121;\n",
       "        border: 4px solid #212121;\n",
       "        box-sizing: border-box;\n",
       "        display: flex;\n",
       "        flex-direction: column;\n",
       "        height: 100%;\n",
       "        justify-content: center;\n",
       "        position: relative;\n",
       "        width: 100%;\n",
       "      `;\n",
       "\n",
       "      const App = () => {\n",
       "        const renderCountRef = useRef(0);\n",
       "        const [_, setRenderCount] = useState(0);\n",
       "\n",
       "        // These are bindings to the 0-9 keys and are milliseconds of timeout per step\n",
       "        const speeds = [\n",
       "          0,\n",
       "          3000,\n",
       "          1000,\n",
       "          500,\n",
       "          333, // Default\n",
       "          200,\n",
       "          100,\n",
       "          50,\n",
       "          25,\n",
       "          10,\n",
       "        ];\n",
       "\n",
       "        const contextRef = useRef({\n",
       "          animate: false,\n",
       "          agents: [],\n",
       "          controls: false,\n",
       "          debug: false,\n",
       "          environment: { steps: [], info: {} },\n",
       "          header: window.innerHeight >= 600,\n",
       "          height: window.innerHeight,\n",
       "          interactive: false,\n",
       "          legend: true,\n",
       "          loading: false,\n",
       "          playing: false,\n",
       "          processing: false,\n",
       "          renderer: () => &quot;DNE&quot;,\n",
       "          settings: false,\n",
       "          speed: speeds[4],\n",
       "          step: 0,\n",
       "          width: window.innerWidth,\n",
       "        });\n",
       "\n",
       "        // Context helpers.\n",
       "        const rerender = (contextRef.current.rerender = () =>\n",
       "          setRenderCount((renderCountRef.current += 1)));\n",
       "        const setStep = (contextRef.current.setStep = (newStep) => {\n",
       "          contextRef.current.step = newStep;\n",
       "          rerender();\n",
       "        });\n",
       "        const setPlaying = (contextRef.current.setPlaying = (playing) => {\n",
       "          contextRef.current.playing = playing;\n",
       "          rerender();\n",
       "        });\n",
       "        const pause = (contextRef.current.pause = () => setPlaying(false));\n",
       "\n",
       "        const playNext = () => {\n",
       "          const context = contextRef.current;\n",
       "\n",
       "          if (\n",
       "            context.playing &&\n",
       "            context.step < context.environment.steps.length - 1\n",
       "          ) {\n",
       "            setStep(context.step + 1);\n",
       "            play(true);\n",
       "          } else {\n",
       "            pause();\n",
       "          }\n",
       "        };\n",
       "\n",
       "        const play = (contextRef.current.play = (continuing) => {\n",
       "          const context = contextRef.current;\n",
       "          if (context.playing && !continuing) return;\n",
       "          if (!context.playing) setPlaying(true);\n",
       "          if (\n",
       "            !continuing &&\n",
       "            context.step === context.environment.steps.length - 1\n",
       "          ) {\n",
       "            setStep(0);\n",
       "          }\n",
       "          setTimeout(playNext, context.speed);\n",
       "        });\n",
       "\n",
       "        const updateContext = (o) => {\n",
       "          const context = contextRef.current;\n",
       "          Object.assign(context, o, {\n",
       "            environment: { ...context.environment, ...(o.environment || {}) },\n",
       "          });\n",
       "          rerender();\n",
       "        };\n",
       "\n",
       "        // First time setup.\n",
       "        useEffect(() => {\n",
       "          // Timeout is used to ensure useEffect renders once.\n",
       "          setTimeout(() => {\n",
       "            // Initialize context with window.kaggle.\n",
       "            updateContext(window.kaggle || {});\n",
       "\n",
       "            if (window.kaggle.playing) {\n",
       "                play(true);\n",
       "            }\n",
       "\n",
       "            // Listen for messages received to update the context.\n",
       "            window.addEventListener(\n",
       "              &quot;message&quot;,\n",
       "              (event) => {\n",
       "                // Ensure the environment names match before updating.\n",
       "                try {\n",
       "                  if (\n",
       "                    event.data.environment.name ==\n",
       "                    contextRef.current.environment.name\n",
       "                  ) {\n",
       "                    updateContext(event.data);\n",
       "                  }\n",
       "                } catch {}\n",
       "              },\n",
       "              false\n",
       "            );\n",
       "            // Listen for keyboard commands.\n",
       "            window.addEventListener(\n",
       "              &quot;keydown&quot;,\n",
       "              (event) => {\n",
       "                const {\n",
       "                  interactive,\n",
       "                  isInteractive,\n",
       "                  playing,\n",
       "                  step,\n",
       "                  environment,\n",
       "                } = contextRef.current;\n",
       "                const key = event.keyCode;\n",
       "                const zero_key = 48\n",
       "                const nine_key = 57\n",
       "                if (\n",
       "                  interactive ||\n",
       "                  isInteractive() ||\n",
       "                  (key !== 32 && key !== 37 && key !== 39 && !(key >= zero_key && key <= nine_key))\n",
       "                )\n",
       "                  return;\n",
       "\n",
       "                if (key === 32) {\n",
       "                  playing ? pause() : play();\n",
       "                } else if (key === 39) {\n",
       "                  contextRef.current.playing = false;\n",
       "                  if (step < environment.steps.length - 1) setStep(step + 1);\n",
       "                  rerender();\n",
       "                } else if (key === 37) {\n",
       "                  contextRef.current.playing = false;\n",
       "                  if (step > 0) setStep(step - 1);\n",
       "                  rerender();\n",
       "                } else if (key >= zero_key && key <= nine_key) {\n",
       "                  contextRef.current.speed = speeds[key - zero_key];\n",
       "                }\n",
       "                event.preventDefault();\n",
       "                return false;\n",
       "              },\n",
       "              false\n",
       "            );\n",
       "          }, 1);\n",
       "        }, []);\n",
       "\n",
       "        if (contextRef.current.debug) {\n",
       "          console.log(&quot;context&quot;, contextRef.current);\n",
       "        }\n",
       "\n",
       "        // Ability to update context.\n",
       "        contextRef.current.update = updateContext;\n",
       "\n",
       "        // Ability to communicate with ipython.\n",
       "        const execute = (contextRef.current.execute = (source) =>\n",
       "          new Promise((resolve, reject) => {\n",
       "            try {\n",
       "              window.parent.IPython.notebook.kernel.execute(source, {\n",
       "                iopub: {\n",
       "                  output: (resp) => {\n",
       "                    const type = resp.msg_type;\n",
       "                    if (type === &quot;stream&quot;) return resolve(resp.content.text);\n",
       "                    if (type === &quot;error&quot;) return reject(new Error(resp.evalue));\n",
       "                    return reject(new Error(&quot;Unknown message type: &quot; + type));\n",
       "                  },\n",
       "                },\n",
       "              });\n",
       "            } catch (e) {\n",
       "              reject(new Error(&quot;IPython Unavailable: &quot; + e));\n",
       "            }\n",
       "          }));\n",
       "\n",
       "        // Ability to return an action from an interactive session.\n",
       "        contextRef.current.act = (action) => {\n",
       "          const id = contextRef.current.environment.id;\n",
       "          updateContext({ processing: true });\n",
       "          execute(`\n",
       "            import json\n",
       "            from kaggle_environments import interactives\n",
       "            if &quot;${id}&quot; in interactives:\n",
       "                action = json.loads('${JSON.stringify(action)}')\n",
       "                env, trainer = interactives[&quot;${id}&quot;]\n",
       "                trainer.step(action)\n",
       "                print(json.dumps(env.steps))`)\n",
       "            .then((resp) => {\n",
       "              try {\n",
       "                updateContext({\n",
       "                  processing: false,\n",
       "                  environment: { steps: JSON.parse(resp) },\n",
       "                });\n",
       "                play();\n",
       "              } catch (e) {\n",
       "                updateContext({ processing: resp.split(&quot;\\n&quot;)[0] });\n",
       "                console.error(resp, e);\n",
       "              }\n",
       "            })\n",
       "            .catch((e) => console.error(e));\n",
       "        };\n",
       "\n",
       "        // Check if currently interactive.\n",
       "        contextRef.current.isInteractive = () => {\n",
       "          const context = contextRef.current;\n",
       "          const steps = context.environment.steps;\n",
       "          return (\n",
       "            context.interactive &&\n",
       "            !context.processing &&\n",
       "            context.step === steps.length - 1 &&\n",
       "            steps[context.step].some((s) => s.status === &quot;ACTIVE&quot;)\n",
       "          );\n",
       "        };\n",
       "\n",
       "        return h`\n",
       "          <${Context.Provider} value=${contextRef.current}>\n",
       "            <${Player} />\n",
       "          <//>`;\n",
       "      };\n",
       "\n",
       "      preact.render(h`<${App} />`, document.body);\n",
       "    </script>\n",
       "  </body>\n",
       "</html>\n",
       "\" width=\"200\" height=\"200\" frameborder=\"0\"></iframe> "
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "env = make('tictactoe', debug=False,\n",
    "           configuration={\"actTimeout\": 1000,\n",
    "                          \"agentTimeout\": 1000,\n",
    "                          \"runTimeout\": 2000})\n",
    "steps = env.run([my_agent, \"reaction\"])\n",
    "env.render(mode='ipython', width=200, height=200)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## Testando o Algoritmo"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "### Profundidade Máxima"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2023-04-12T21:31:47.507537Z",
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     "shell.execute_reply.started": "2023-04-12T21:31:47.507495Z"
    },
    "jupyter": {
     "outputs_hidden": false
    },
    "pycharm": {
     "name": "#%%\n"
    },
    "trusted": true
   },
   "outputs": [],
   "source": [
    "def check_winner(tabuleiro):\n",
    "    # checa colunas\n",
    "    for i in range(3):\n",
    "        if tabuleiro[i] == tabuleiro[i + 3] == tabuleiro[i + 6] and tabuleiro[i] != 0:\n",
    "            return tabuleiro[i]\n",
    "    # checa linhas\n",
    "    for i in range(0, 9, 3):\n",
    "        if tabuleiro[i] == tabuleiro[i + 1] == tabuleiro[i + 2] and tabuleiro[i] != 0:\n",
    "            return tabuleiro[i]\n",
    "    # checa diagonais (as duas)\n",
    "    if (tabuleiro[0] == tabuleiro[4] == tabuleiro[8] or tabuleiro[2] == tabuleiro[4] == tabuleiro[6]) and tabuleiro[\n",
    "        4] != 0:\n",
    "        return tabuleiro[4]\n",
    "    return 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2023-04-12T21:31:47.519901Z",
     "iopub.status.busy": "2023-04-12T21:31:47.519080Z",
     "iopub.status.idle": "2023-04-12T21:31:47.532179Z",
     "shell.execute_reply": "2023-04-12T21:31:47.530659Z",
     "shell.execute_reply.started": "2023-04-12T21:31:47.519845Z"
    },
    "jupyter": {
     "outputs_hidden": false
    },
    "pycharm": {
     "name": "#%%\n"
    },
    "trusted": true
   },
   "outputs": [],
   "source": [
    "def my_agent_profmax(obs,reward):\n",
    "    p = 9\n",
    "    player = obs['mark']\n",
    "    v,acao = max_value(obs['board'],p,player,None)\n",
    "    return acao"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2023-04-12T21:31:47.534937Z",
     "iopub.status.busy": "2023-04-12T21:31:47.534396Z",
     "iopub.status.idle": "2023-04-12T21:31:47.547262Z",
     "shell.execute_reply": "2023-04-12T21:31:47.545902Z",
     "shell.execute_reply.started": "2023-04-12T21:31:47.534884Z"
    },
    "jupyter": {
     "outputs_hidden": false
    },
    "pycharm": {
     "name": "#%%\n"
    },
    "trusted": true
   },
   "outputs": [],
   "source": [
    "def reaction_test(iter, agent):\n",
    "    runtime = list()\n",
    "    winners = list()\n",
    "    for i in range(iter):\n",
    "        start_time = time.time()\n",
    "        env = make('tictactoe', debug=False,\n",
    "           configuration={\"actTimeout\": 1000,\n",
    "                          \"agentTimeout\": 1000,\n",
    "                          \"runTimeout\": 2000})\n",
    "        steps = env.run([agent, \"reaction\"])\n",
    "        end_time = time.time()\n",
    "        runtime.append(end_time - start_time)\n",
    "        winner = check_winner(steps[-1][0]['observation']['board'])\n",
    "        winners.append(winner)\n",
    "    return runtime, winners\n",
    "\n",
    "def random_test(iter, agent):\n",
    "    runtime = list()\n",
    "    winners = list()\n",
    "    for i in range(iter):\n",
    "        start_time = time.time()\n",
    "        env = make('tictactoe', debug=False,\n",
    "           configuration={\"actTimeout\": 1000,\n",
    "                          \"agentTimeout\": 1000,\n",
    "                          \"runTimeout\": 2000})\n",
    "        steps = env.run([agent, \"random\"])\n",
    "        end_time = time.time()\n",
    "        runtime.append(end_time - start_time)\n",
    "        winner = check_winner(steps[-1][0]['observation']['board'])\n",
    "        winners.append(winner)\n",
    "    return runtime, winners"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2023-04-12T21:31:47.550116Z",
     "iopub.status.busy": "2023-04-12T21:31:47.549483Z",
     "iopub.status.idle": "2023-04-12T22:30:18.750853Z",
     "shell.execute_reply": "2023-04-12T22:30:18.749435Z",
     "shell.execute_reply.started": "2023-04-12T21:31:47.550067Z"
    },
    "jupyter": {
     "outputs_hidden": false
    },
    "pycharm": {
     "name": "#%%\n"
    },
    "trusted": true
   },
   "outputs": [],
   "source": [
    "runtime_random, winners_random = random_test(200, my_agent_profmax)\n",
    "runtime_reaction, winners_reaction = reaction_test(200, my_agent_profmax)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2023-04-12T22:30:18.753001Z",
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     "shell.execute_reply": "2023-04-12T22:30:19.192929Z",
     "shell.execute_reply.started": "2023-04-12T22:30:18.752961Z"
    },
    "jupyter": {
     "outputs_hidden": false
    },
    "pycharm": {
     "name": "#%%\n"
    },
    "trusted": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set()\n",
    "sns.histplot(runtime_random, label='Random')\n",
    "sns.histplot(runtime_reaction, label='Reaction')\n",
    "plt.title('Tempo de execução')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2023-04-12T22:30:19.196878Z",
     "iopub.status.busy": "2023-04-12T22:30:19.196305Z",
     "iopub.status.idle": "2023-04-12T22:30:19.204755Z",
     "shell.execute_reply": "2023-04-12T22:30:19.203384Z",
     "shell.execute_reply.started": "2023-04-12T22:30:19.196816Z"
    },
    "jupyter": {
     "outputs_hidden": false
    },
    "pycharm": {
     "name": "#%%\n"
    },
    "trusted": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Runtime médio para cada agente: \n",
      "Random:  8.776627901792526\n",
      "Reaction:  8.779284777641296\n"
     ]
    }
   ],
   "source": [
    "# get average runtime\n",
    "print('Runtime médio para cada agente: ')\n",
    "print('Random: ', sum(runtime_random)/len(runtime_random))\n",
    "print('Reaction: ', sum(runtime_reaction)/len(runtime_reaction))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2023-04-12T22:30:19.207165Z",
     "iopub.status.busy": "2023-04-12T22:30:19.206439Z",
     "iopub.status.idle": "2023-04-12T22:30:19.505523Z",
     "shell.execute_reply": "2023-04-12T22:30:19.504255Z",
     "shell.execute_reply.started": "2023-04-12T22:30:19.207113Z"
    },
    "jupyter": {
     "outputs_hidden": false
    },
    "pycharm": {
     "name": "#%%\n"
    },
    "trusted": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "reaction_win = winners_reaction.count(1)\n",
    "reaction_loss = winners_reaction.count(2)\n",
    "reaction_draw = winners_reaction.count(0)\n",
    "\n",
    "table = pd.DataFrame({'Reaction': [reaction_win, reaction_loss, reaction_draw]}, index=['Win', 'Loss', 'Draw'])\n",
    "table.plot(kind='bar')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2023-04-12T22:30:19.507730Z",
     "iopub.status.busy": "2023-04-12T22:30:19.507345Z",
     "iopub.status.idle": "2023-04-12T22:30:19.738992Z",
     "shell.execute_reply": "2023-04-12T22:30:19.737572Z",
     "shell.execute_reply.started": "2023-04-12T22:30:19.507694Z"
    },
    "jupyter": {
     "outputs_hidden": false
    },
    "pycharm": {
     "name": "#%%\n"
    },
    "trusted": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "random_win = winners_random.count(1)\n",
    "random_loss = winners_random.count(2)\n",
    "random_draw = winners_random.count(0)\n",
    "\n",
    "table = pd.DataFrame({'Random': [random_win, random_loss, random_draw]}, index=['Win', 'Loss', 'Draw'])\n",
    "table.plot(kind='bar')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "### Testando o Algoritmo com Profundidade 4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2023-04-12T22:30:19.741292Z",
     "iopub.status.busy": "2023-04-12T22:30:19.740911Z",
     "iopub.status.idle": "2023-04-12T22:30:19.747785Z",
     "shell.execute_reply": "2023-04-12T22:30:19.746396Z",
     "shell.execute_reply.started": "2023-04-12T22:30:19.741254Z"
    },
    "jupyter": {
     "outputs_hidden": false
    },
    "pycharm": {
     "name": "#%%\n"
    },
    "trusted": true
   },
   "outputs": [],
   "source": [
    "def my_agent_prof3(obs,reward):\n",
    "    p = 3\n",
    "    player = obs['mark']\n",
    "    v,acao = max_value(obs['board'],p,player,None)\n",
    "    return acao"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2023-04-12T22:30:19.749689Z",
     "iopub.status.busy": "2023-04-12T22:30:19.749240Z",
     "iopub.status.idle": "2023-04-12T22:31:06.910855Z",
     "shell.execute_reply": "2023-04-12T22:31:06.909078Z",
     "shell.execute_reply.started": "2023-04-12T22:30:19.749650Z"
    },
    "jupyter": {
     "outputs_hidden": false
    },
    "pycharm": {
     "name": "#%%\n"
    },
    "trusted": true
   },
   "outputs": [],
   "source": [
    "runtime_random, winners_random = random_test(200, my_agent_prof3)\n",
    "runtime_reaction, winners_reaction = reaction_test(200, my_agent_prof3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2023-04-12T22:31:06.916671Z",
     "iopub.status.busy": "2023-04-12T22:31:06.916183Z",
     "iopub.status.idle": "2023-04-12T22:31:08.102143Z",
     "shell.execute_reply": "2023-04-12T22:31:08.100340Z",
     "shell.execute_reply.started": "2023-04-12T22:31:06.916627Z"
    },
    "jupyter": {
     "outputs_hidden": false
    },
    "pycharm": {
     "name": "#%%\n"
    },
    "trusted": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set()\n",
    "sns.histplot(runtime_random, label='Random')\n",
    "sns.histplot(runtime_reaction, label='Reaction')\n",
    "plt.title('Tempo de execução')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2023-04-12T22:31:08.103990Z",
     "iopub.status.busy": "2023-04-12T22:31:08.103613Z",
     "iopub.status.idle": "2023-04-12T22:31:08.112125Z",
     "shell.execute_reply": "2023-04-12T22:31:08.110652Z",
     "shell.execute_reply.started": "2023-04-12T22:31:08.103947Z"
    },
    "jupyter": {
     "outputs_hidden": false
    },
    "pycharm": {
     "name": "#%%\n"
    },
    "trusted": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Runtime médio para cada agente: \n",
      "Random:  0.11500784873962402\n",
      "Reaction:  0.12072125911712646\n"
     ]
    }
   ],
   "source": [
    "# get average runtime\n",
    "print('Runtime médio para cada agente: ')\n",
    "print('Random: ', sum(runtime_random)/len(runtime_random))\n",
    "print('Reaction: ', sum(runtime_reaction)/len(runtime_reaction))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2023-04-12T22:31:08.114362Z",
     "iopub.status.busy": "2023-04-12T22:31:08.114016Z",
     "iopub.status.idle": "2023-04-12T22:31:08.371769Z",
     "shell.execute_reply": "2023-04-12T22:31:08.370374Z",
     "shell.execute_reply.started": "2023-04-12T22:31:08.114330Z"
    },
    "jupyter": {
     "outputs_hidden": false
    },
    "pycharm": {
     "name": "#%%\n"
    },
    "trusted": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "reaction_win = winners_reaction.count(1)\n",
    "reaction_loss = winners_reaction.count(2)\n",
    "reaction_draw = winners_reaction.count(0)\n",
    "\n",
    "table = pd.DataFrame({'Reaction': [reaction_win, reaction_loss, reaction_draw]}, index=['Win', 'Loss', 'Draw'])\n",
    "table.plot(kind='bar')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2023-04-12T22:31:08.373592Z",
     "iopub.status.busy": "2023-04-12T22:31:08.373230Z",
     "iopub.status.idle": "2023-04-12T22:31:08.615145Z",
     "shell.execute_reply": "2023-04-12T22:31:08.613820Z",
     "shell.execute_reply.started": "2023-04-12T22:31:08.373556Z"
    },
    "jupyter": {
     "outputs_hidden": false
    },
    "pycharm": {
     "name": "#%%\n"
    },
    "trusted": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "random_win = winners_random.count(1)\n",
    "random_loss = winners_random.count(2)\n",
    "random_draw = winners_random.count(0)\n",
    "\n",
    "table = pd.DataFrame({'Random': [random_win, random_loss, random_draw]}, index=['Win', 'Loss', 'Draw'])\n",
    "table.plot(kind='bar')\n",
    "plt.show()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Perguntas que você precisa responder:\n",
    "\n",
    "1 - Qual é o agente com melhor desempenho? MinMax sem limite de profundidade ou com limite de profundidade? Justifique a sua resposta.\n",
    "\n",
    "\n",
    "2 - Qual é o agente mais rápido? É significantemente mais rápido? Justifique a sua resposta."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Respostas    \n",
    "    \n",
    "    1 - O agente com o melhor desempenho acabou sendo o com o limite de profundidade. Isso fica evidente ao analisarmos os gráficos de tempo de execução e resultados dos experimentos. O primeiro algoritmo (sem limite) acaba empatando a maioria das partidas com o algoritmo de reaction do Kaggle, e ganhando a maioria dos jogos contra o random agent. Além disso, seu tempo de execução média girava em torno dos 8.7 segundos. Já o com limite de profundidade não só rodava muito mais rapidamente como também tinha melhores resultados, ganhando mais de 80% dos jogos contra o reaction agent e saindo invicto contra o random. Portanto, acho que é possível afirmar que o agente com limite de profundidade é o melhor entre os dois. \n",
    "\n",
    "    2 - O agente mais rápido seria aquele que retornaria uma jogada mais rapidamente, em menos tempo de processamento. O agente sem limite de profundidade (profundidade máxima) demorou de 8 a 9 segundos para jogar uma partida inteira contra os agentes do Kaggle. Agora, quando implementamos um limite de profundidade (nesse caso, 4), vemos que o agente roda significantemente mais rápido, tendo uma média entre 0.10 e 0.15 segundos. Isso nos mostra que, claramente, o agente mais rápido é o com limite de profundidade. \n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
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