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Environments for Multi-Agent Systems

First International Workshop, E4MAS, 2004, New York, NY, July 19, 2004, Revised Selected Papers

  • Conference proceedings
  • © 2005

Overview

Editors:
  1. Danny Weyns

    1. DistriNet Labs, K.U. Leuven, Belgium

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  2. H. Dyke Parunak

    1. NewVectors, Ann Arbor, USA

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    You can also search for this editor in PubMed   Google Scholar

  3. Fabien Michel

    1. MODECO-CReSTIC, Université de Reims, Reims, France

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    You can also search for this editor in PubMed   Google Scholar

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 3374)

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

Included in the following conference series:

Conference proceedings info: E4MAS 2004.

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About this book

The modern ?eld of multiagent systems has developed from two main lines of earlier research. Its practitioners generally regard it as a form of arti?cial intelligence (AI). Some of its earliest work was reported in a series of workshops in the US dating from1980,revealinglyentitled,“DistributedArti?cialIntelligence,”andpioneers often quoted a statement attributed to Nils Nilsson that “all AI is distributed. ” The locus of classical AI was what happens in the head of a single agent, and much MAS research re?ects this heritage with its emphasis on detailed modeling of the mental state and processes of individual agents. From this perspective, intelligenceisultimatelythepurviewofasinglemind,thoughitcanbeampli?ed by appropriate interactions with other minds. These interactions are typically mediated by structured protocols of various sorts, modeled on human conver- tional behavior. But the modern ?eld of MAS was not born of a single parent. A few - searchershavepersistentlyadvocatedideasfromthe?eldofarti?ciallife(ALife). These scientists were impressed by the complex adaptive behaviors of commu- ties of animals (often extremely simple animals, such as insects or even micro- ganisms). The computational models on which they drew were often created by biologists who used them not to solve practical engineering problems but to test their hypotheses about the mechanisms used by natural systems. In the ar- ?cial life model, intelligence need not reside in a single agent, but emerges at the level of the community from the nonlinear interactions among agents. - cause the individual agents are often subcognitive, their interactions cannot be modeled by protocols that presume linguistic competence.

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Table of contents (14 papers)

  1. Front Matter

    Download chapter PDF

  2. Survey

    1. Environments for Multiagent Systems State-of-the-Art and Research Challenges

      • Danny Weyns, H. Van Dyke Parunak, Fabien Michel, Tom Holvoet, Jacques Ferber
      Pages 1-47

  3. Conceptual Models

    1. AGRE: Integrating Environments with Organizations

      • J. Ferber, F. Michel, J. Baez
      Pages 48-56

    2. From Reality to Mind: A Cognitive Middle Layer of Environment Concepts for Believable Agents

      • Paul Hsueh-Min Chang, Kuang-Tai Chen, Yu-Hung Chien, Edward Kao, Von-Wun Soo
      Pages 57-73

    3. A Spatially Dependent Communication Model for Ubiquitous Systems

      • Stefania Bandini, Sara Manzoni, Giuseppe Vizzari
      Pages 74-90

  4. Languages for Design and Specification

    1. ELMS: An Environment Description Language for Multi-agent Simulation

      • Fabio Y. Okuyama, Rafael H. Bordini, Antônio Carlos da Rocha Costa
      Pages 91-108

    2. MIC*: A Deployment Environment for Autonomous Agents

      • Abdelkader Gouaïch, Fabien Michel, Yves Guiraud
      Pages 109-126

  5. Simulation and Environments

    1. About the Role of the Environment in Multi-agent Simulations

      • Franziska Klügl, Manuel Fehler, Rainer Herrler
      Pages 127-149

    2. Modelling Environments for Distributed Simulation

      • Michael Lees, Brian Logan, Rob Minson, Ton Oguara, Georgios Theodoropoulos
      Pages 150-167

  6. Mediated Coordination

    1. Supporting Context-Aware Interaction in Dynamic Multi-agent Systems

      • Christine Julien, Gruia-Catalin Roman
      Pages 168-189

    2. Environment-Based Coordination Through Coordination Artifacts

      • Alessandro Ricci, Mirko Viroli, Andrea Omicini
      Pages 190-214

    3. “Exhibitionists” and “Voyeurs” Do It Better: A Shared Environment for Flexible Coordination with Tacit Messages

      • Luca Tummolini, Cristiano Castelfranchi, Alessandro Ricci, Mirko Viroli, Andrea Omicini
      Pages 215-231

  7. Applications

    1. Swarming Distributed Pattern Detection and Classification

      • Sven A. Brueckner, H. Van Dyke Parunak
      Pages 232-245

    2. Digital Pheromones for Coordination of Unmanned Vehicles

      • H. Van Dyke Parunak, Sven A. Brueckner, John Sauter
      Pages 246-263

    3. Motion Coordination in the Quake 3 Arena Environment: A Field-Based Approach

      • Marco Mamei, Franco Zambonelli
      Pages 264-278

  8. Back Matter

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Other volumes

  1. Environments for Multi-Agent Systems

Editors and Affiliations

  • DistriNet Labs, K.U. Leuven, Belgium

    Danny Weyns

  • NewVectors, Ann Arbor, USA

    H. Dyke Parunak

  • MODECO-CReSTIC, Université de Reims, Reims, France

    Fabien Michel

Bibliographic Information

  • Book Title: Environments for Multi-Agent Systems

  • Book Subtitle: First International Workshop, E4MAS, 2004, New York, NY, July 19, 2004, Revised Selected Papers

  • Editors: Danny Weyns, H. Dyke Parunak, Fabien Michel

  • Series Title: Lecture Notes in Computer Science

  • DOI: https://doi.org/10.1007/b106134

  • Publisher: Springer Berlin, Heidelberg

  • eBook Packages: Computer Science, Computer Science (R0)

  • Copyright Information: Springer-Verlag Berlin Heidelberg 2005

  • Softcover ISBN: 978-3-540-24575-9Published: 10 February 2005

  • eBook ISBN: 978-3-540-32259-7Published: 18 February 2005

  • Series ISSN: 0302-9743

  • Series E-ISSN: 1611-3349

  • Edition Number: 1

  • Number of Pages: X, 279

  • Topics: Artificial Intelligence, Computer Communication Networks

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