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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

The infinite horizons

The first assumption is the infinite horizons, that is, the infinite amount of time steps to reach goal state from start state. Therefore,

The policy function doesn't take the remaining time steps into consideration. If it had been a finite horizon, then the policy would have been,

 

where t is the time steps left to get the task done.

Therefore, without the assumption of the infinite horizon, the notion of policy would not be stationary, that is, , rather it would be .

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Publisher Resources

ISBN: 9781788835725Supplemental Content