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portada Reinforcement Learning Algorithms: Analysis and Applications
Type
Physical Book
Illustrated by
Publisher
Author
Language
English
Pages
206
Format
Paperback
Dimensions
23.4x15.6x1.2 cm
Weight
0.31 kg.
ISBN13
9783030411909
Categories

Reinforcement Learning Algorithms: Analysis and Applications

Boris Belousov (Illustrated by) · Hany Abdulsamad (Illustrated by) · Pascal Klink (Illustrated by) · Springer · Paperback

Reinforcement Learning Algorithms: Analysis and Applications - Belousov, Boris ; Abdulsamad, Hany ; Klink, Pascal

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Synopsis "Reinforcement Learning Algorithms: Analysis and Applications "

Prediction Error and Actor-Critic Hypotheses in the Brain.- Reviewing on-policy / off-policy critic learning in the context of Temporal Differences 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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