목록DeepReinforcementLearning (1)
On the journey of
[Deep Reinforcement Learning Hands On] Chapter.02
2.1 The Anatomy of the Agent 2.1.1 A Simplistic Situation Define an environment that gives the agent random rewards for a limited number of steps, regardless of the agent’s actions class Environment: def __init__(self): self.steps_left = 10 # initialize its internal state def get_observation(self): return [0.0, 0.0, 0.0] def get_actions(self): return [0, 1] # agent가 실행할 수 있는 동작의 집합 def is_done(s..
Experiences & Study/이브와(KIBWA)
2023. 8. 4. 09:16