Add an example of using the Roshambo bot population.

PiperOrigin-RevId: 478490385
Change-Id: I5860f5cc509a8372389e0c64e321b210afbde0c5

open_spiel/python/examples/roshambo_population_example.py

@@ -0,0 +1,153 @@
+# Copyright 2022 DeepMind Technologies Limited
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""Simple example of using the Roshambo population.
+
+Note: the Roshambo bots are an optional dependency and excluded by default.
+To enable Roshambo bots, set OPEN_SPIEL_BUILD_WITH_ROSHAMBO to ON when building.
+See
+https://github.com/deepmind/open_spiel/blob/master/docs/install.md#configuring-conditional-dependencies
+for details.
+"""
+
+from absl import app
+from absl import flags
+import numpy as np
+
+from open_spiel.python import games  # pylint: disable=unused-import
+from open_spiel.python import rl_agent
+from open_spiel.python import rl_environment
+import pyspiel
+
+FLAGS = flags.FLAGS
+
+flags.DEFINE_integer("player0_pop_id", 0, "Population member ID for player 0")
+flags.DEFINE_integer("player1_pop_id", 1, "Population member ID for player 1")
+flags.DEFINE_integer("seed", 0, "Seed to use for RNG")
+flags.DEFINE_integer("env_recall", 1,
+                     "Number of recent steps to include in observation")
+
+
+class BotAgent(rl_agent.AbstractAgent):
+  """Agent class that wraps a bot.
+
+  Note, the environment must include the OpenSpiel state in its observations,
+  which means it must have been created with use_full_state=True.
+  """
+
+  def __init__(self, num_actions, bot, name="bot_agent"):
+    assert num_actions > 0
+    self._bot = bot
+    self._num_actions = num_actions
+
+  def restart(self):
+    self._bot.restart()
+
+  def step(self, time_step, is_evaluation=False):
+    # If it is the end of the episode, don't select an action.
+    if time_step.last():
+      return
+
+    _, state = pyspiel.deserialize_game_and_state(
+        time_step.observations["serialized_state"])
+
+    action = self._bot.step(state)
+    probs = np.zeros(self._num_actions)
+    probs[action] = 1.0
+
+    return rl_agent.StepOutput(action=action, probs=probs)
+
+
+def eval_agents(env, agents, num_players, num_episodes):
+  """Evaluate the agent."""
+  sum_episode_rewards = np.zeros(num_players)
+  for ep in range(num_episodes):
+    for agent in agents:
+      # Bots need to be restarted at the start of the episode.
+      if hasattr(agent, "restart"):
+        agent.restart()
+    time_step = env.reset()
+    episode_rewards = np.zeros(num_players)
+    while not time_step.last():
+      agents_output = [
+          agent.step(time_step, is_evaluation=True) for agent in agents
+      ]
+      action_list = [agent_output.action for agent_output in agents_output]
+      time_step = env.step(action_list)
+      episode_rewards += time_step.rewards
+    sum_episode_rewards += episode_rewards
+    print(f"Finished episode {ep}, "
+          + f"avg returns: {sum_episode_rewards / num_episodes}")
+
+  return sum_episode_rewards / num_episodes
+
+
+def print_roshambo_bot_names_and_ids(roshambo_bot_names):
+  print("Roshambo bot population:")
+  for i in range(len(roshambo_bot_names)):
+    print(f"{i}: {roshambo_bot_names[i]}")
+
+
+def create_roshambo_bot_agent(player_id, num_actions, bot_names, pop_id):
+  name = bot_names[pop_id]
+  # Creates an OpenSpiel bot with the default number of throws
+  # (pyspiel.ROSHAMBO_NUM_THROWS). To create one for a different number of
+  # throws per episode, add the number as the third argument here.
+  bot = pyspiel.make_roshambo_bot(player_id, name)
+  return BotAgent(num_actions, bot, name=name)
+
+
+def main(_):
+  np.random.seed(FLAGS.seed)
+
+  # Note that the include_full_state variable has to be enabled because the
+  # BotAgent needs access to the full state.
+  env = rl_environment.Environment(
+      "repeated_game(stage_game=matrix_rps(),num_repetitions=" +
+      f"{pyspiel.ROSHAMBO_NUM_THROWS}," +
+      f"recall={FLAGS.env_recall})",
+      include_full_state=True)
+  num_players = 2
+  num_actions = env.action_spec()["num_actions"]
+  # Learning agents might need this:
+  # info_state_size = env.observation_spec()["info_state"][0]
+
+  print("Loading population...")
+  pop_size = pyspiel.ROSHAMBO_NUM_BOTS
+  print(f"Population size: {pop_size}")
+  roshambo_bot_names = pyspiel.roshambo_bot_names()
+  roshambo_bot_names.sort()
+  print_roshambo_bot_names_and_ids(roshambo_bot_names)
+
+  bot_id = 0
+  roshambo_bot_ids = {}
+  for name in roshambo_bot_names:
+    roshambo_bot_ids[name] = bot_id
+    bot_id += 1
+
+  # Create two bot agents
+  agents = [
+      create_roshambo_bot_agent(0, num_actions, roshambo_bot_names,
+                                FLAGS.player0_pop_id),
+      create_roshambo_bot_agent(1, num_actions, roshambo_bot_names,
+                                FLAGS.player1_pop_id)
+  ]
+
+  print("Starting eval run")
+  avg_eval_returns = eval_agents(env, agents, num_players, 100)
+  print(avg_eval_returns)
+
+
+if __name__ == "__main__":
+  app.run(main)

open_spiel/python/pybind11/bots.cc

@@ -296,7 +296,9 @@ void init_pyspiel_bots(py::module& m) {
   // no arguments; returns vector of strings
   m.def("roshambo_bot_names", open_spiel::roshambo::RoshamboBotNames);
   // args: player_int (int), bot name (string), num throws (int), returns bot
-  m.def("make_roshambo_bot", open_spiel::roshambo::MakeRoshamboBot);
+  m.def("make_roshambo_bot", open_spiel::roshambo::MakeRoshamboBot,
+        py::arg("player_id"), py::arg("bot_name"),
+        py::arg("num_throws") = open_spiel::roshambo::kNumThrows);
 #endif
 }
 }  // namespace open_spiel