LEADER 04964nam 22006255 450 001 9910767548903321 005 20251226200219.0 024 7 $a10.1007/b106134 035 $a(CKB)1000000000212843 035 $a(SSID)ssj0000317522 035 $a(PQKBManifestationID)11224120 035 $a(PQKBTitleCode)TC0000317522 035 $a(PQKBWorkID)10293919 035 $a(PQKB)11169680 035 $a(DE-He213)978-3-540-32259-7 035 $a(MiAaPQ)EBC3067605 035 $a(PPN)123092051 035 $a(EXLCZ)991000000000212843 100 $a20100704d2005 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aEnvironments for Multi-Agent Systems $eFirst International Workshop, E4MAS, 2004, New York, NY, July 19, 2004, Revised Selected Papers /$fedited by Danny Weyns, H. Van Dyke Parunak, Fabien Michel 205 $a1st ed. 2005. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2005. 215 $a1 online resource (X, 279 p.) 225 1 $aLecture Notes in Artificial Intelligence,$x2945-9141 ;$v3374 300 $aBibliographic Level Mode of Issuance: Monograph 311 08$a3-540-32259-0 311 08$a3-540-24575-8 320 $aIncludes bibliographical references and index. 327 $aSurvey -- Environments for Multiagent Systems State-of-the-Art and Research Challenges -- Conceptual Models -- AGRE: Integrating Environments with Organizations -- From Reality to Mind: A Cognitive Middle Layer of Environment Concepts for Believable Agents -- A Spatially Dependent Communication Model for Ubiquitous Systems -- Languages for Design and Specification -- ELMS: An Environment Description Language for Multi-agent Simulation -- MIC*: A Deployment Environment for Autonomous Agents -- Simulation and Environments -- About the Role of the Environment in Multi-agent Simulations -- Modelling Environments for Distributed Simulation -- Mediated Coordination -- Supporting Context-Aware Interaction in Dynamic Multi-agent Systems -- Environment-Based Coordination Through Coordination Artifacts -- ?Exhibitionists? and ?Voyeurs? Do It Better: A Shared Environment for Flexible Coordination with Tacit Messages -- Applications -- Swarming Distributed Pattern Detection and Classification -- Digital Pheromones for Coordination of Unmanned Vehicles -- Motion Coordination in the Quake 3 Arena Environment: A Field-Based Approach. 330 $aThe modern ?eld of multiagent systems has developed from two main lines of earlier research. Its practitioners generally regard it as a form of arti?cial intelligence (AI). Some of its earliest work was reported in a series of workshops in the US dating from1980,revealinglyentitled,?DistributedArti?cialIntelligence,?andpioneers often quoted a statement attributed to Nils Nilsson that ?all AI is distributed. ? The locus of classical AI was what happens in the head of a single agent, and much MAS research re?ects this heritage with its emphasis on detailed modeling of the mental state and processes of individual agents. From this perspective, intelligenceisultimatelythepurviewofasinglemind,thoughitcanbeampli?ed by appropriate interactions with other minds. These interactions are typically mediated by structured protocols of various sorts, modeled on human conver- tional behavior. But the modern ?eld of MAS was not born of a single parent. A few - searchershavepersistentlyadvocatedideasfromthe?eldofarti?ciallife(ALife). These scientists were impressed by the complex adaptive behaviors of commu- ties of animals (often extremely simple animals, such as insects or even micro- ganisms). The computational models on which they drew were often created by biologists who used them not to solve practical engineering problems but to test their hypotheses about the mechanisms used by natural systems. In the ar- ?cial life model, intelligence need not reside in a single agent, but emerges at the level of the community from the nonlinear interactions among agents. - cause the individual agents are often subcognitive, their interactions cannot be modeled by protocols that presume linguistic competence. 410 0$aLecture Notes in Artificial Intelligence,$x2945-9141 ;$v3374 606 $aArtificial intelligence 606 $aComputer networks 606 $aArtificial Intelligence 606 $aComputer Communication Networks 615 0$aArtificial intelligence. 615 0$aComputer networks. 615 14$aArtificial Intelligence. 615 24$aComputer Communication Networks. 676 $a006.3/3 701 $aWeyns$b Danny$0867840 701 $aParunak$b H. Van Dyke$01750747 701 $aMichel$b Fabien$01750748 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910767548903321 996 $aEnvironments for multi-agent systems$94194435 997 $aUNINA