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Layered Learning in Multiagent Systems A Winning Approach to Robotic Soccer cover
  • ISBN: 9780262194389
  • ISBN10: 0262194384

Layered Learning in Multiagent Systems A Winning Approach to Robotic Soccer

by Peter Stone

  • List Price: $50.00
  • Binding: Hardcover
  • Publisher: Mit Pr
  • Publish date: 03/01/2000
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Description
This book looks at multiagent systems that consist of teams of autonomous agents acting in real-time, noisy, collaborative, and adversarial environments. The book makes four main contributions to the fields of machine learning and multiagent systems.

First, it describes an architecture within which a flexible team structure allows member agents to decompose a task into flexible roles and to switch roles while acting. Second, it presents layered learning, a general-purpose machine-learning method for complex domains in which learning a mapping directly from 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 cannot necessarily observe the state-changes caused by other agents' actions. The final contribution is a fully functioning multi-agent system that incorporates learning in a realtime, noisy domain with teammates and adversaries -- a computer-simulated robotic soccer team.

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