Read Layered Learning in Multiagent Systems: A Winning Approach to Robotic Soccer

Layered Learning in Multiagent Systems: A Winning Approach to Robotic Soccer

Peter Stone

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Description:This book looks at multiagent systems that consist of teams of autonomous agentsacting in real-time, noisy, collaborative, and adversarial environments. The book makes four maincontributions to the fields of machine learning and multiagent systems.First, it describes anarchitecture within which a flexible team structure allows member agents to decompose a task intoflexible roles and to switch roles while acting. Second, it presents layered learning, ageneral-purpose machine-learning method for complex domains in which learning a mapping directlyfrom agents' sensors to their actuators is intractable with existing machine-learning methods.Third, the book introduces a new multiagent reinforcement learning algorithm--team-partitioned,opaque-transition reinforcement learning (TPOT-RL)--designed for domains in which agents cannotnecessarily observe the state-changes caused by other agents' actions. The final contribution is afully functioning multiagent system that incorporates learning in a real-time, noisy domain withteammates and adversaries--a computer-simulated robotic soccer team.Peter Stone's work is the basisfor the CMUnited Robotic Soccer Team, which has dominated recent RoboCup competitions. RoboCup notonly helps roboticists to prove their theories in a realistic situation, but has drawn considerablepublic and professional attention to the field of intelligent robotics. The CMUnited team won the1999 Stockholm simulator competition, outscoring its opponents by the rather impressive cumulativescore of 110-0.We have made it easy for you to find a PDF Ebooks without any digging. And by having access to our ebooks online or by storing it on your computer, you have convenient answers with Layered Learning in Multiagent Systems: A Winning Approach to Robotic Soccer. To get started finding Layered Learning in Multiagent Systems: A Winning Approach to Robotic Soccer, you are right to find our website which has a comprehensive collection of manuals listed.
Our library is the biggest of these that have literally hundreds of thousands of different products represented.

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Format: PDF, EPUB & Kindle Edition

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ISBN: 0262264609

Description: This book looks at multiagent systems that consist of teams of autonomous agentsacting in real-time, noisy, collaborative, and adversarial environments. The book makes four maincontributions to the fields of machine learning and multiagent systems.First, it describes anarchitecture within which a flexible team structure allows member agents to decompose a task intoflexible roles and to switch roles while acting. Second, it presents layered learning, ageneral-purpose machine-learning method for complex domains in which learning a mapping directlyfrom agents' sensors to their actuators is intractable with existing machine-learning methods.Third, the book introduces a new multiagent reinforcement learning algorithm--team-partitioned,opaque-transition reinforcement learning (TPOT-RL)--designed for domains in which agents cannotnecessarily observe the state-changes caused by other agents' actions. The final contribution is afully functioning multiagent system that incorporates learning in a real-time, noisy domain withteammates and adversaries--a computer-simulated robotic soccer team.Peter Stone's work is the basisfor the CMUnited Robotic Soccer Team, which has dominated recent RoboCup competitions. RoboCup notonly helps roboticists to prove their theories in a realistic situation, but has drawn considerablepublic and professional attention to the field of intelligent robotics. The CMUnited team won the1999 Stockholm simulator competition, outscoring its opponents by the rather impressive cumulativescore of 110-0.We have made it easy for you to find a PDF Ebooks without any digging. And by having access to our ebooks online or by storing it on your computer, you have convenient answers with Layered Learning in Multiagent Systems: A Winning Approach to Robotic Soccer. To get started finding Layered Learning in Multiagent Systems: A Winning Approach to Robotic Soccer, you are right to find our website which has a comprehensive collection of manuals listed.
Our library is the biggest of these that have literally hundreds of thousands of different products represented.

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Layered Learning in Multiagent Systems: A Winning Approach to Robotic Soccer

Layered Learning in Multiagent Systems: A Winning Approach to Robotic Soccer

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