Environments for Multi-Agent Systems: First International Workshop, E4MAS, 2004, New York, NY, July 19, 2004, Revised Selected Papers, Volume 1 (Google eBook)

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Danny Weyns, H. Van Dyke Parunak, Fabien Michel
Springer Science & Business Media, Feb 10, 2005 - Computers - 278 pages
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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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Contents

Environments for Multiagent Systems StateoftheArt and Research Challenges
1
Integrating Environments with Organizations
48
A Cognitive Middle Layer of Environment Concepts for Believable Agents
57
A Spatially Dependent Communication Model for Ubiquitous Systems
74
An Environment Description Language for Multiagent Simulation
91
A Deployment Environment for Autonomous Agents
109
About the Role of the Environment in Multiagent Simulations
127
Modelling Environments for Distributed Simulation
150
Supporting ContextAware Interaction in Dynamic Multiagent Systems
168
EnvironmentBased Coordination Through Coordination Artifacts
190
A Shared Environment for Flexible Coordination with Tacit Messages
215
Swarming Distributed Pattern Detection and Classification
232
Digital Pheromones for Coordination of Unmanned Vehicles
246
A FieldBased Approach
264
Author Index
279
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