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Artificial Life and Intelligent Agents

First International Symposium, ALIA 2014, Bangor, UK, November 5-6, 2014. Revised Selected Papers

  • Christopher J. Headleand
  • William J. Teahan
  • Llyr Ap Cenydd
Conference proceedings ALIA 2014

Part of the Communications in Computer and Information Science book series (CCIS, volume 519)

Table of contents

  1. Front Matter
    Pages I-XI
  2. Learning and Evolution

    1. Front Matter
      Pages 1-1
    2. Christopher J. Headleand, Gareth Henshall, Llyr Ap Cenydd, William J. Teahan
      Pages 3-16
    3. Aparajit Narayan, Elio Tuci, Frédéric Labrosse
      Pages 17-30
    4. Olalekan Lanihun, Bernie Tiddeman, Elio Tuci, Patricia Shaw
      Pages 31-43
    5. Daan Bloembergen, Ipek Caliskanelli, Karl Tuyls
      Pages 44-58
  3. Human Interaction

    1. Front Matter
      Pages 59-59
    2. Daniel Claes, Karl Tuyls
      Pages 61-72
    3. Tibor Bosse, Charlotte Gerritsen, Jeroen de Man, Suzanne Tolmeijer
      Pages 80-93
  4. Robotic Simulation

    1. Front Matter
      Pages 95-95
    2. Simon Jones, Matthew Studley, Alan Winfield
      Pages 97-109
    3. Steve Battle
      Pages 110-123
    4. Ipek Caliskanelli, Bastian Broecker, Karl Tuyls
      Pages 124-140
  5. Back Matter
    Pages 141-141

About these proceedings

Introduction

This book constitutes the refereed proceedings of the First International Symposium on Artificial Life and Intelligent Agents, ALIA 2014, held in Bangor, UK, in November 2014. The 10 revised full papers were carefully reviewed and selected from 20 submissions. The papers are organized in topical sections on learning and evolution; human interaction; robotic simulation.

Keywords

agent simulation models artificial intelligence cognitive robotics computer vision control methods cooperation and coordination distributed artificial intelligence evolutionary robotics intelligent agents machine learning multi-agent planning multi-agent systems multi-task learning planning and scheduling reinforcement learning robotic planning search methodologies supervised learning unsupervised learning vision for robotics

Editors and affiliations

  • Christopher J. Headleand
    • 1
  • William J. Teahan
    • 2
  • Llyr Ap Cenydd
    • 3
  1. 1.Bangor UniversityBangorUnited Kingdom
  2. 2.Bangor UniversityBangorUnited Kingdom
  3. 3.Bangor UniversityBangorUnited Kingdom

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-18084-7
  • Copyright Information Springer International Publishing Switzerland 2015
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-18083-0
  • Online ISBN 978-3-319-18084-7
  • Series Print ISSN 1865-0929
  • Series Online ISSN 1865-0937
  • Buy this book on publisher's site
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