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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

Open questions

Following is a list of open, non-exhaustive questions that demand special care to deliver better reinforcement learning models in the field of robotics:

  • How do we automate the process of state-action space representation?
    • State-action spaces in robotics is continuous and multi-dimensional. The high-dimensionality and continuous nature of the state and action space makes the process of representation selection difficult to automate.
    • State approximation is also an open question to deal with and is under intense study.
  • How do we generate a reward function from the data received?
    • The success of a reinforcement learning algorithm is highly dependent on the quality of the reward function, its coverage of different state representation, ...
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Publisher Resources

ISBN: 9781788835725Supplemental Content