LEADER 06589nam 22007695 450 001 996465961003316 005 20200704023253.0 010 $a3-540-32243-4 010 $a3-540-25262-2 024 7 $a10.1007/b106991 035 $a(CKB)1000000000212881 035 $a(SSID)ssj0000319057 035 $a(PQKBManifestationID)11236902 035 $a(PQKBTitleCode)TC0000319057 035 $a(PQKBWorkID)10336530 035 $a(PQKB)10206783 035 $a(DE-He213)978-3-540-32243-6 035 $a(MiAaPQ)EBC3067869 035 $a(PPN)123093023 035 $a(EXLCZ)991000000000212881 100 $a20100715d2005 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aMulti-Agent and Multi-Agent-Based Simulation$b[electronic resource] $eJoint Workshop MABS 2004 /$fedited by Paul Davidsson, Brian Logan, Keiki Takadama 205 $a1st ed. 2005. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2005. 215 $a1 online resource (X, 265 p.) 225 1 $aLecture Notes in Artificial Intelligence ;$v3415 300 $aBibliographic Level Mode of Issuance: Monograph 311 08$aPrinted edition: 9783540252627 320 $aIncludes bibliographical references and index. 327 $aSimulation of Multi-agent Systems -- Smooth Scaling Ahead: Progressive MAS Simulation from Single PCs to Grids -- Agent Communication in Distributed Simulations -- Distributed Simulation of MAS -- Extending Time Management Support for Multi-agent Systems -- Designing and Implementing MABS in AKIRA -- Technique and Technology -- Work-Environment Analysis: Environment Centric Multi-agent Simulation for Design of Socio-technical Systems -- Layering Social Interaction Scenarios on Environmental Simulation -- Change Your Tags Fast! ? A Necessary Condition for Cooperation? -- Users Matter: A Multi-agent Systems Model of High Performance Computing Cluster Users -- Formal Analysis of Meeting Protocols -- Methodology and Modelling -- From KISS to KIDS ? An ?Anti-simplistic? Modelling Approach -- Analysis of Learning Types in an Artificial Market -- Toward Guidelines for Modeling Learning Agents in Multiagent-Based Simulation: Implications from Q-Learning and Sarsa Agents -- Social Dynamics -- Agent-Based Modelling of Forces in Crowds -- An Investigation into the Use of Group Dynamics for Solving Social Dilemmas -- Applications -- ASAP: Agent-Based Simulator for Amusement Park -- Patchiness and Prosociality: An Agent-Based Model of Plio/Pleistocene Hominid Food Sharing -- Plant Disease Incursion Management -- A Hybrid Micro-Simulator for Determining the Effects of Governmental Control Policies on Transport Chains -- Simulation and Analysis of Shared Extended Mind. 330 $aThis volume presents revised and extended versions of selected papers presented at the Joint Workshop on Multi-Agent and Multi-Agent-Based Simulation, a workshop federated with the 3rd International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2004), which was held in New York City, USA, July 19?23, 2004. The workshop was in part a continuation of the International Workshop on Multi-Agent-Based Simulation (MABS) series. - vised versions of papers presented at the four previous MABS workshops have been published as volumes 1534, 1979, 2581, and 2927 in the Lecture Notes in Arti?cial Intelligence series. The aim of the workshop was to provide a forum for work in both appli- tions of multi-agent-based simulation and the technical challenges of simulating large multi-agent systems (MAS). There has been considerable recent progress in modelling and analyzing multi-agent systems, and in techniques that apply MAS models to complex real-world systems such as social systems and organi- tions. Simulation is an increasingly important strand that weaves together this work. In high-risk, high-cost situations, simulations provide critical cost/bene?t leverage, and make possible explorations that cannot be carried out in situ: ? Multi-agentapproachestosimulatingcomplexsystemsarekeytoolsinint- disciplinary studies of social systems. Agent-based social simulation (ABSS) researchsimulatesandsynthesizessocialbehaviorinordertounderstandreal social systems with properties of self-organization, scalability, robustness, and openness. ? IntheMAScommunity,simulationhasbeenappliedtoawiderangeofMAS research and design problems, from models of complex individual agents - ploying sophisticated internal mechanisms to models of large-scale societies of relatively simple agents which focus more on the interactions between agents. 410 0$aLecture Notes in Artificial Intelligence ;$v3415 606 $aSystem theory 606 $aArtificial intelligence 606 $aComputer simulation 606 $aComputer communication systems 606 $aApplication software 606 $aSystems Theory, Control$3https://scigraph.springernature.com/ontologies/product-market-codes/M13070 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 606 $aSimulation and Modeling$3https://scigraph.springernature.com/ontologies/product-market-codes/I19000 606 $aComputer Communication Networks$3https://scigraph.springernature.com/ontologies/product-market-codes/I13022 606 $aComputer Appl. in Social and Behavioral Sciences$3https://scigraph.springernature.com/ontologies/product-market-codes/I23028 606 $aInformation Systems Applications (incl. Internet)$3https://scigraph.springernature.com/ontologies/product-market-codes/I18040 615 0$aSystem theory. 615 0$aArtificial intelligence. 615 0$aComputer simulation. 615 0$aComputer communication systems. 615 0$aApplication software. 615 14$aSystems Theory, Control. 615 24$aArtificial Intelligence. 615 24$aSimulation and Modeling. 615 24$aComputer Communication Networks. 615 24$aComputer Appl. in Social and Behavioral Sciences. 615 24$aInformation Systems Applications (incl. Internet). 676 $a519 702 $aDavidsson$b Paul$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aLogan$b Brian$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aTakadama$b Keiki$4edt$4http://id.loc.gov/vocabulary/relators/edt 906 $aBOOK 912 $a996465961003316 996 $aMulti-Agent and Multi-Agent-Based Simulation$9772697 997 $aUNISA