Skip to main content
SpringerLink
Log in

Adaptive and Learning Agents

AAMAS 2011 International Workshop, ALA 2011, Taipei, Taiwan, May 2, 2011, Revised Selected Papers

  • Conference proceedings
  • © 2012

Overview

Editors:
  1. Peter Vrancx

    1. AI& Computational Modeling Lab, Vrije Universiteit Brussel, Brussel, Belgium

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  2. Matthew Knudson

    1. NASA Ames Research Park, Carnegie Mellon University, Moffet Field, USA

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  3. Marek Grześ

    1. School of Computer Science, University of Waterloo, Waterloo, Canada

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  • Fast-track conference proceedings
  • State-of-the-art research
  • Up-to-date results

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 7113)

Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)

Included in the following conference series:

Conference proceedings info: ALA 2011.

This is a preview of subscription content, log in via an institution to check access.

Access this book

Log in via an institution
eBook USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

Licence this eBook for your library

Institutional subscriptions

Table of contents (8 papers)

  1. Front Matter

    Download chapter PDF

  2. Invited Contribution

    1. Co-learning Segmentation in Marketplaces

      • Edward Robinson, Peter McBurney, Xin Yao
      Pages 1-20

  3. Workshop Contributions

    1. Reinforcement Learning Transfer via Common Subspaces

      • Haitham Bou Ammar, Matthew E. Taylor
      Pages 21-36

    2. A Convergent Multiagent Reinforcement Learning Approach for a Subclass of Cooperative Stochastic Games

      • Thomas Kemmerich, Hans Kleine Büning
      Pages 37-53

    3. Multi-agent Reinforcement Learning for Simulating Pedestrian Navigation

      • Francisco Martinez-Gil, Miguel Lozano, Fernando Fernández
      Pages 54-69

    4. Leveraging Domain Knowledge to Learn Normative Behavior: A Bayesian Approach

      • Hadi Hosseini, Mihaela Ulieru
      Pages 70-84

    5. Basis Function Discovery Using Spectral Clustering and Bisimulation Metrics

      • Gheorghe Comanici, Doina Precup
      Pages 85-99

    6. Heterogeneous Populations of Learning Agents in the Minority Game

      • David Catteeuw, Bernard Manderick
      Pages 100-113

    7. Solving Sparse Delayed Coordination Problems in Multi-Agent Reinforcement Learning

      • Yann-Michaël De Hauwere, Peter Vrancx, Ann Nowé
      Pages 114-133

  4. Back Matter

    Download chapter PDF
Back to top

Keywords

About this book

This volume constitutes the thoroughly refereed post-conference proceedings of the International Workshop on Adaptive and Learning Agents, ALA 2011, held at the 10th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2011, in Taipei, Taiwan, in May 2011. The 7 revised full papers presented together with 1 invited talk were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on single and multi-agent reinforcement learning, supervised multiagent learning, adaptation and learning in dynamic environments, learning trust and reputation, minority games and agent coordination.

Editors and Affiliations

  • AI& Computational Modeling Lab, Vrije Universiteit Brussel, Brussel, Belgium

    Peter Vrancx

  • NASA Ames Research Park, Carnegie Mellon University, Moffet Field, USA

    Matthew Knudson

  • School of Computer Science, University of Waterloo, Waterloo, Canada

    Marek Grześ

Bibliographic Information

Publish with us

Policies and ethics

Back to top

Search

Navigation