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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

Issues due to model uncertainty

In order to avoid the cost associated with real-world interactions, simulators are used. The catch is that the simulating model should be close to a real-world scenario. For an ideal setting, the approach is to perform the learning tasks in the simulation and transfer the knowledge model to the robot. Creating a good accurate learning model for the robot and the simulating environment model of the real-world scenario is highly challenging as it requires a huge amount of real-world data samples.

Small models learned on small sets of data leads to under-modeling, causing the robot to diverge easily from the real-world system. The issue with the simulators is that they can't replicate the real-world complexities ...

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Publisher Resources

ISBN: 9781788835725Supplemental Content