29 lines
931 B
Python
29 lines
931 B
Python
import numpy as np
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class evaluator(object):
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def __init__(self, env, action_num):
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self.env = env
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self.action_num = action_num
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def __call__(self, state):
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raise NotImplementedError("Need to implement the evaluator")
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class rollout_policy(evaluator):
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def __init__(self, env, action_num):
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super(rollout_policy, self).__init__(env, action_num)
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self.is_terminated = False
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def __call__(self, state):
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# TODO: prior for rollout policy
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total_reward = 0.
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action = np.random.randint(0, self.action_num)
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state, reward = self.env.step_forward(state, action)
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total_reward += reward
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while state is not None:
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action = np.random.randint(0, self.action_num)
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state, reward = self.env.step_forward(state, action)
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total_reward += reward
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return np.ones([self.action_num])/self.action_num, total_reward
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