Page 1
Page 1
img

Environments for Multi-Agent Systems III ; 3rd International Workshop, E4MAS 2006, Hakodate, Japan, May 8, 2006, Selected Revised and Invited Papers

This book are organized in topical sections on models, architecture, and design, mediated interaction and stigmery, governing environment, and applications.

img

Environments for Multi-Agent Systems II ; 2nd International Workshop, E4MAS 2005, Utrecht, The Netherlands, July 25, 2005, Selected Revised and Invited Papers

This book constitutes the thoroughly refereed post-proceedings of the Second International Workshop on Environments for Multiagent Systems, E4MAS 2005, held in July 2005. The 16 revised papers presented were carefully reviewed and selected from the lectures given at the workshop.

img

Environments for Multi-Agent Systems ; 1st International Workshop, E4MAS, 2004, New York, NY, July 19, 2004, Revised Selected Papers

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.

img

Engineering Environment-Mediated Multi-Agent Systems ; International Workshop, EEMMAS 2007, Dresden, Germany, October 5, 2007. Selected Revised and Invited Papers

This book constitutes the thoroughly refereed proceedings of the International Workshop on Engineering Environment-Mediated Multi-Agent Systems, held in Dresden,The volume includes 16 thoroughly revised papers, selected from the lectures given at the workshop, together with 2 papers resulting from invited talks by prominent researchers in the field. The papers are organized in sections on engineering self-organizing applications, stigmergic interaction, modeling and structuring mediating environments, and environment-based support for context and organizations.

Results Per Page