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keon / deep-q-learning

Minimal Deep Q Learning (DQN & DDQN) implementations in Keras
https://keon.io/deep-q-learning
MIT License
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missing the initialization of target action value and refreshing the Qhat #13

Open fi000 opened 6 years ago

fi000 commented 6 years ago

I have several questions: 1- When I compared with algorithm presented in"Human-level control through deep reinforcement learning", I can not find the third initialization (initial target action value)? Also, I do not find the last step "every C step Qhat=Q"? Would you please explain where are them or what is the difference to reach them? These steps seems essential! 2- I have my own environment, If I want to have a state=[a,b,c] as input instead of just one input for DQN showing the state what I should do?

WorksWellWithOthers commented 3 years ago
  1. There is a function updating the target model. Does this answer your question?
  2. How about, state = [[a, b, c]] ?