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| 001 | 978-3-540-32243-6 | ||
| 003 | DE-He213 | ||
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_a9783540322436 _9978-3-540-32243-6 |
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| 024 | 7 |
_a10.1007/b106991 _2doi |
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| 050 | 4 | _aQA402.3-402.37 | |
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_aMulti-Agent and Multi-Agent-Based Simulation _h[electronic resource] : _bJoint Workshop MABS 2004 / _cedited by Paul Davidsson, Brian Logan, Keiki Takadama. |
| 250 | _a1st ed. 2005. | ||
| 264 | 1 |
_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg : _bImprint: Springer, _c2005. |
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| 300 |
_aX, 265 p. _bonline resource. |
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| 336 |
_atext _btxt _2rdacontent |
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| 337 |
_acomputer _bc _2rdamedia |
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| 338 |
_aonline resource _bcr _2rdacarrier |
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| 347 |
_atext file _bPDF _2rda |
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| 490 | 1 |
_aLecture Notes in Artificial Intelligence, _x2945-9141 ; _v3415 |
|
| 505 | 0 | _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. | |
| 520 | _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 relativelysimple agents which focus more on the interactions between agents. | ||
| 650 | 0 | _aSystem theory. | |
| 650 | 0 | _aControl theory. | |
| 650 | 0 | _aArtificial intelligence. | |
| 650 | 0 | _aComputer simulation. | |
| 650 | 0 | _aComputer networks . | |
| 650 | 0 |
_aSocial sciences _xData processing. |
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| 650 | 0 | _aApplication software. | |
| 650 | 1 | 4 | _aSystems Theory, Control. |
| 650 | 2 | 4 | _aArtificial Intelligence. |
| 650 | 2 | 4 | _aComputer Modelling. |
| 650 | 2 | 4 | _aComputer Communication Networks. |
| 650 | 2 | 4 | _aComputer Application in Social and Behavioral Sciences. |
| 650 | 2 | 4 | _aComputer and Information Systems Applications. |
| 700 | 1 |
_aDavidsson, Paul. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt |
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| 700 | 1 |
_aLogan, Brian. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt |
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| 700 | 1 |
_aTakadama, Keiki. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt |
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| 710 | 2 | _aSpringerLink (Online service) | |
| 773 | 0 | _tSpringer Nature eBook | |
| 776 | 0 | 8 |
_iPrinted edition: _z9783540252627 |
| 776 | 0 | 8 |
_iPrinted edition: _z9783540808749 |
| 830 | 0 |
_aLecture Notes in Artificial Intelligence, _x2945-9141 ; _v3415 |
|
| 856 | 4 | 0 | _uhttps://doi.org/10.1007/b106991 |
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