Adaptive and Learning Agents [electronic resource] : Second Workshop, ALA 2009, Held as Part of the AAMAS 2009 Conference in Budapest, Hungary, May 12, 2009. Revised Selected Papers / edited by Matthew E. Taylor, Karl Tuyls.
By: Taylor, Matthew E [editor.].
Contributor(s): Tuyls, Karl [editor.] | SpringerLink (Online service).
Material type:
BookSeries: Lecture Notes in Computer Science: 5924Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2010Description: 154p. 70 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783642118142.Subject(s): Computer science | Computer network architectures | Computer Communication Networks | Computer software | Computational complexity | Artificial intelligence | Computer simulation | Computer Science | Artificial Intelligence (incl. Robotics) | Computer Communication Networks | Discrete Mathematics in Computer Science | Algorithm Analysis and Problem Complexity | Simulation and Modeling | Computer Systems Organization and Communication NetworksDDC classification: 006.3 Online resources: Click here to access online Abstraction and Generalization in Reinforcement Learning: A Summary and Framework -- The Effects of Evolved Sociability in a Commons Dilemma -- Replicator Dynamics for Multi-agent Learning: An Orthogonal Approach -- Decentralized Learning in Wireless Sensor Networks -- Recursive Adaptation of Stepsize Parameter for Non-stationary Environments -- Multiagent Reinforcement Learning Model for the Emergence of Common Property and Transhumance in Sub-Saharan Africa -- Learning to Locate Trading Partners in Agent Networks -- Coordinating Learning Agents for Multiple Resource Job Scheduling.
This volume constitutes the thoroughly refereed post-conference proceedings of the Second Workshop on Adaptive and Learning Agents, ALA 2009, held as part of the AAMAS 2009 conference in Budapest, Hungary, in May 2009. The 8 revised full papers presented were carefully reviewed and selected from numerous submissions. They cover a variety of themes: single and multi-agent reinforcement learning, the evolution and emergence of cooperation in agent systems, sensor networks and coordination in multi-resource job scheduling.
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