Reinforcement learning algorithms : analysis and applications

Reinforcement learning algorithms : analysis and applications / Boris Belousov, Hany Abdulsamad, Pascal Klink, Simone Parisi, Jan Peters, editors.

This book reviews research developments in diverse areas of reinforcement learning such as model-free actor-critic methods, model-based learning and control, information geometry of policy searches, reward design, and exploration in biology and the behavioral sciences. Special emphasis is placed on...

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Bibliographic Details
Other Authors: Belousov, Boris (Editor), Abdulsamad, Hany (Editor), Klink, Pascal (Editor), Parisi, Simone (Editor), Peters, Jan, 1976- (Editor)
Format: eBook
Language:English
Published: Cham, Switzerland : Springer, [2021]
Series:Studies in computational intelligence ; v. 883.
Subjects:
Reinforcement learning.
Algorithms.
algorithms.
Algorithms
Reinforcement learning
Online Access:Click for online access
Table of Contents:
  • Prediction Error and Actor-Critic Hypotheses in the Brain
  • Reviewing on-policy / o-policy critic learning in the context of Temporal Dierences and Residual Learning
  • Reward Function Design in Reinforcement Learning
  • Exploration Methods In Sparse Reward Environments
  • A Survey on Constraining Policy Updates Using the KL Divergence
  • Fisher Information Approximations in Policy Gradient Methods
  • Benchmarking the Natural gradient in Policy Gradient Methods and Evolution Strategies
  • Information-Loss-Bounded Policy Optimization
  • Persistent Homology for Dimensionality Reduction
  • Model-free Deep Reinforcement Learning Algorithms and Applications
  • Actor vs Critic
  • Bring Color to Deep Q-Networks
  • Distributed Methods for Reinforcement Learning
  • Model-Based Reinforcement Learning
  • Challenges of Model Predictive Control in a Black Box Environment
  • Control as Inference?

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