Explore the latest books of this year!
Bookbot

Hierarchical Relative Entropy Policy Search

An Information Theoretic Learning Algorithm in Multimodal Solution Spaces for Real Robots

Parameters

  • 68 pages
  • 3 hours of reading

More about the book

The book explores the significance of hierarchical structures in enhancing scalability and performance in motor skill tasks. It introduces the concept of a "mixed option policy," where a gating network selects which option to execute, followed by an option-policy that determines the action. This hierarchical approach enables the learning of multiple solutions to problems. The algorithm is grounded in an innovative information theoretic policy search method that effectively manages the exploitation-exploration trade-off, minimizing information loss during policy updates.

Book purchase

Hierarchical Relative Entropy Policy Search, Christian Daniel, Gerhard Neumann

Language
Released
2014
product-detail.submit-box.info.binding
(Paperback)
We’ll email you as soon as we track it down.

Payment methods

No one has rated yet.Add rating