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| import sys
import gym import numpy as np import gym.spaces
class MyEnv(gym.Env): FIELD_TYPES = [ 'S', 'G', ' ', '山', '☆', ] MAP = np.array([ [0, 3, 3, 2, 3, 2, 3, 1], [2, 3, 2, 2, 3, 2, 3, 2], [2, 2, 2, 2, 3, 2, 2, 2], [3, 2, 3, 3, 3, 2, 2, 3], [3, 2, 3, 2, 2, 2, 2, 2], [2, 2, 2, 2, 3, 2, 2, 3], [3, 3, 2, 2, 3, 3, 2, 2], [3, 3, 3, 2, 3, 3, 2, 3] ]) MAX_STEPS = 200
def __init__(self): super().__init__() self.action_space = gym.spaces.Discrete(4) self.observation_space = gym.spaces.Box( low=0, high=len(self.FIELD_TYPES), shape=self.MAP.shape ) self.reset()
def reset(self): self.pos = self._find_pos('S')[0] self.goal = self._find_pos('G')[0] self.done = False self.steps = 0 return self._observe()
def step(self, action): if action == 0: next_pos = self.pos + [0, 1] elif action == 1: next_pos = self.pos + [0, -1] elif action == 2: next_pos = self.pos + [1, 0] elif action == 3: next_pos = self.pos + [-1, 0]
if self._is_movable(next_pos): self.pos = next_pos moved = True else: moved = False
observation = self._observe() reward = self._get_reward(self.pos, moved) self.done = self._is_done() return observation, reward, self.done, {}
def render(self, mode='console', close=False): for row in self._observe(): for elem in row: print(self.FIELD_TYPES[elem], end='') print()
def _close(self): pass
def _seed(self, seed=None): pass
def _get_reward(self, pos, moved): if moved and (self.goal == pos).all(): return 100 else: return -1
def _is_movable(self, pos): return ( 0 <= pos[0] < self.MAP.shape[0] and 0 <= pos[1] < self.MAP.shape[1] and self.FIELD_TYPES[self.MAP[tuple(pos)]] != '山' )
def _observe(self): observation = self.MAP.copy() observation[tuple(self.pos)] = self.FIELD_TYPES.index('☆') return observation
def _is_done(self): if (self.pos == self.goal).all(): return True elif self.steps > self.MAX_STEPS: return True else: return False
def _find_pos(self, field_type): return np.array(list(zip(*np.where(self.MAP == self.FIELD_TYPES.index(field_type)))))
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