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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

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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Table of contents (14 papers)

  1. Survey

  2. Conceptual Models

  3. Languages for Design and Specification

  4. Simulation and Environments

  5. Mediated Coordination

  6. Applications

Other volumes

  1. Environments for Multi-Agent Systems

Keywords

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.

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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