Environments for Multi-Agent Systems

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

  • Danny Weyns
  • H. Van Dyke Parunak
  • Fabien Michel
Conference proceedings E4MAS 2004

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

Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 3374)

Table of contents

  1. Front Matter
  2. Survey

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

    1. J. Ferber, F. Michel, J. Baez
      Pages 48-56
    2. Paul Hsueh-Min Chang, Kuang-Tai Chen, Yu-Hung Chien, Edward Kao, Von-Wun Soo
      Pages 57-73
    3. Stefania Bandini, Sara Manzoni, Giuseppe Vizzari
      Pages 74-90
  4. Languages for Design and Specification

    1. Fabio Y. Okuyama, Rafael H. Bordini, Antônio Carlos da Rocha Costa
      Pages 91-108
    2. Abdelkader Gouaïch, Fabien Michel, Yves Guiraud
      Pages 109-126
  5. Simulation and Environments

    1. Franziska Klügl, Manuel Fehler, Rainer Herrler
      Pages 127-149
    2. Michael Lees, Brian Logan, Rob Minson, Ton Oguara, Georgios Theodoropoulos
      Pages 150-167
  6. Mediated Coordination

    1. Christine Julien, Gruia-Catalin Roman
      Pages 168-189
    2. Alessandro Ricci, Mirko Viroli, Andrea Omicini
      Pages 190-214
    3. Luca Tummolini, Cristiano Castelfranchi, Alessandro Ricci, Mirko Viroli, Andrea Omicini
      Pages 215-231
  7. Applications

    1. Sven A. Brueckner, H. Van Dyke Parunak
      Pages 232-245
    2. H. Van Dyke Parunak, Sven A. Brueckner, John Sauter
      Pages 246-263
  8. Back Matter

About these proceedings


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.


AI agents ALife ALife agents adaptive agents agent communication agent environments artificial intelligence autonomous agents classification distributed artificial intelligence environment-based coordination intelligence multi-agent simulation multi-agent system multiagent systems

Editors and affiliations

  • Danny Weyns
    • 1
  • H. Van Dyke Parunak
    • 2
  • Fabien Michel
    • 3
  1. 1.DistriNet LabsK.U. LeuvenBelgium
  2. 2.NewVectorsAnn ArborUSA
  3. 3.MODECO-CReSTICUniversité de ReimsReimsFrance

Bibliographic information