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38 lines
898 B
Python
38 lines
898 B
Python
"""
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Simple environment with known optimal policy and value function.
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This environment has just two actions.
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Action 0 yields 0 reward and then terminates the session.
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Action 1 yields 1 reward and then terminates the session.
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Optimal policy: action 1.
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Optimal value function: v(0)=1 (there is only one state, state 0)
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"""
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import gym
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import random
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from gym import spaces
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class OneRoundDeterministicRewardEnv(gym.Env):
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def __init__(self):
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self.action_space = spaces.Discrete(2)
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self.observation_space = spaces.Discrete(1)
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self._reset()
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def _step(self, action):
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assert self.action_space.contains(action)
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if action:
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reward = 1
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else:
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reward = 0
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done = True
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return self._get_obs(), reward, done, {}
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def _get_obs(self):
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return 0
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def _reset(self):
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return self._get_obs()
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