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Hands-On Reinforcement Learning with Python
book

Hands-On Reinforcement Learning with Python

by Sudharsan Ravichandiran
June 2018
Intermediate to advanced
318 pages
9h 24m
English
Packt Publishing
Content preview from Hands-On Reinforcement Learning with Python

Chapter 9

  1. DRQN makes use of recurrent neural network (RNN) where DQN makes use of vanilla neural network.
  2. DQN is not used applied when the MDP is partially observable.
  3. Refer section Doom with DRQN.
  4. DARQN makes use of attention mechanism unlike DRQN.
  5. DARQN is used to understand and focus on particular area of game screen which is more important.
  6. Soft and hard attention.
  7. We set living reward to 0 which the agent does for each move, even though the move is not useful.
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Publisher Resources

ISBN: 9781788836524