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@jonasschneider @instance01 @joschu @gdb @stevenschmatz @hunkim @tlbtlbtlb @pzhokhov @gvsi @last-g @likefrankie @cclauss
import sys
from contextlib import closing
import numpy as np
from io import StringIO
from gym import utils
from gym.envs.toy_text import discrete
LEFT = 0
DOWN = 1
UP = 3
MAPS = {
"4x4": ["SFFF", "FHFH", "FFFH", "HFFG"],
"8x8": [
def generate_random_map(size=8, p=0.8):
"""Generates a random valid map (one that has a path from start to goal)
:param size: size of each side of the grid
:param p: probability that a tile is frozen
valid = False
# DFS to check that it's a valid path.
def is_valid(res):
frontier, discovered = [], set()
frontier.append((0, 0))
while frontier:
r, c = frontier.pop()
if not (r, c) in discovered:
discovered.add((r, c))
directions = [(1, 0), (0, 1), (-1, 0), (0, -1)]
for x, y in directions:
r_new = r + x
c_new = c + y
if r_new < 0 or r_new >= size or c_new < 0 or c_new >= size:
if res[r_new][c_new] == "G":
return True
if res[r_new][c_new] != "H":
frontier.append((r_new, c_new))
return False
while not valid:
p = min(1, p)
res = np.random.choice(["F", "H"], (size, size), p=[p, 1 - p])
res[0][0] = "S"
res[-1][-1] = "G"
valid = is_valid(res)
return ["".join(x) for x in res]
class FrozenLakeEnv(discrete.DiscreteEnv):
Winter is here. You and your friends were tossing around a frisbee at the
park when you made a wild throw that left the frisbee out in the middle of
the lake. The water is mostly frozen, but there are a few holes where the
ice has melted. If you step into one of those holes, you'll fall into the
freezing water. At this time, there's an international frisbee shortage, so
it's absolutely imperative that you navigate across the lake and retrieve
the disc. However, the ice is slippery, so you won't always move in the
direction you intend.
The surface is described using a grid like the following
S : starting point, safe
F : frozen surface, safe
H : hole, fall to your doom
G : goal, where the frisbee is located
The episode ends when you reach the goal or fall in a hole.
You receive a reward of 1 if you reach the goal, and zero otherwise.
metadata = {"render.modes": ["human", "ansi"]}
def __init__(self, desc=None, map_name="4x4", is_slippery=True):
if desc is None and map_name is None:
desc = generate_random_map()
elif desc is None:
desc = MAPS[map_name]
self.desc = desc = np.asarray(desc, dtype="c")
self.nrow, self.ncol = nrow, ncol = desc.shape
self.reward_range = (0, 1)
nA = 4
nS = nrow * ncol
isd = np.array(desc == b"S").astype("float64").ravel()
isd /= isd.sum()
P = {s: {a: [] for a in range(nA)} for s in range(nS)}
def to_s(row, col):
return row * ncol + col
def inc(row, col, a):
if a == LEFT:
col = max(col - 1, 0)
elif a == DOWN:
row = min(row + 1, nrow - 1)
elif a == RIGHT:
col = min(col + 1, ncol - 1)
elif a == UP:
row = max(row - 1, 0)
return (row, col)
def update_probability_matrix(row, col, action):
newrow, newcol = inc(row, col, action)
newstate = to_s(newrow, newcol)
newletter = desc[newrow, newcol]
done = bytes(newletter) in b"GH"
reward = float(newletter == b"G")
return newstate, reward, done
for row in range(nrow):
for col in range(ncol):
s = to_s(row, col)
for a in range(4):
li = P[s][a]
letter = desc[row, col]
if letter in b"GH":
li.append((1.0, s, 0, True))
if is_slippery:
for b in [(a - 1) % 4, a, (a + 1) % 4]:
(1.0 / 3.0, *update_probability_matrix(row, col, b))
li.append((1.0, *update_probability_matrix(row, col, a)))
super(FrozenLakeEnv, self).__init__(nS, nA, P, isd)
def render(self, mode="human"):
outfile = StringIO() if mode == "ansi" else sys.stdout
row, col = self.s // self.ncol, self.s % self.ncol
desc = self.desc.tolist()
desc = [[c.decode("utf-8") for c in line] for line in desc]
desc[row][col] = utils.colorize(desc[row][col], "red", highlight=True)
if self.lastaction is not None:
" ({})\n".format(["Left", "Down", "Right", "Up"][self.lastaction])
outfile.write("\n".join("".join(line) for line in desc) + "\n")
if mode != "human":
with closing(outfile):
return outfile.getvalue()