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An Information Theoretic Learning Algorithm in Multimodal Solution Spaces for Real Robots
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.
Herman the German"This fascinating and amusing account of his life is told by a colorful and highly capable German who became one of America's most successful technical managers in the development of jet engines for aircraft."-David S. Lewis ChairmanGeneral Dynamics Corporation "Not only has Gerhard Neumann's life been filled with exotic and exciting adventures, but he was a highly successful engineer and executive-truly a superior individual and one of my favorite people."-Sanford N. McDonnellChairman, McDonnell Douglas Corporation "Readers of Gerhard's book will probably come to the same conclusion I formed while doing business with him; there is still room in industry for free spirits." -T. A. WilsonChairman, The Boeing Company