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Reinforcement Learning with TensorFlow
book

Reinforcement Learning with TensorFlow

by Sayon Dutta
April 2018
Intermediate to advanced content levelIntermediate to advanced
334 pages
10h 18m
English
Packt Publishing
Content preview from Reinforcement Learning with TensorFlow

Rewards

The reward of the state quantifies the usefulness of entering into a state. There are three different forms to represent the reward namely, R(s), R(s, a) and R(s, a, s'), but they are all equivalent. 

For a particular environment, the domain knowledge plays an important role in the assignment of rewards for different states as minor changes in the reward do matter for finding the optimal solution to an MDP problem. 

There are two approaches we reward our agent for when taking a certain action. They are:

  • Credit assignment problem: We look at the past and check which actions led to the present reward, that is, which action gets the credit
  • Delayed rewards: In contrast, in the present state, we check which action to take that will lead ...
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Publisher Resources

ISBN: 9781788835725Supplemental Content