Multi-Agent Systems and Applications: 9th ECCAI Advanced Course ACAI 2001 and Agent Link's 3rd European Agent Systems Summer School, EASSS 2001, Prague, Czech Republic, July 2-13, 2001. Selected Tutorial PapersMichael Luck Springer Science & Business Media, 2001/06/20 - 435 ページ The Advanced Course on Artificial Intelligence ACAI 2001 with the subtitle M ulti- Agent Systems and Their Applications , held in Prague, Czech Republic, was a joint event of ECCAI (the European Coordinating Committee for Artificial Intelligence) and AgentLink, the European Network of Excellence for Agent-Based Computing. Whereas ECCAI organizes two-week ACAI courses on different topics every second year, AgentLink s European Agent Systems Summer School (EASSS) has been an annual event since 1999. This year, both of these important events were merged together, giving weight to the fact that multi-agent systems currently represent one of the hottest topics in AI research. The name, ACAI 2001 Summer School, is intended to emphasize that this event continues the tradition of regular ECCAI activities (ACAI), as well as the EASSS summer schools of AgentLink. The Prague ACAI Summer School was proposed and initiated by both the Gerstner Laboratory, Czech Technical University, Prague (GL-CTU) and the Czech Society for Cybernetics and Informatics (CSKI), with the support of the Austrian Research Institute for Artificial Intelligence in Vienna (OFAI). Part of our motivation was catalyzed by experience gained in 1992 during the International Summer School Advanced Topics in Artificial Intelligence (see Springer s LNAI vol. 617) which was organized by the same Czech and Austrian bodies. One of the most important stimulating factors behind the organization of ACAI 2001 was the support provided by the European Commission to the Gerstner Laboratory within the frame of the MIRACLE Center of Excellence project (IST No. |
目次
Foundations of Multiagent Systems | 1 |
Gasser | 15 |
K Sycara | 45 |
W van der Hoek | 73 |
Y Labrou | 96 |
Distributed Problem Solving and Planning | 118 |
Automated Negotiation and Decision Making in Multiagent Environments | 150 |
Agents Advanced Features for Negotiation and Coordination | 173 |
The Practice 123 | 123 |
Plot Planning and Act Planning 173 | 173 |
Directors Planning 229 | 229 |
Camera Planning 255 | 255 |
Light Color and Role Planning 287 | 287 |
Table of Contents | 1 |
Beeri | 30 |
J Meseguer N MartíOliet | 48 |
Social Behaviour Metareasoning and Learning | 187 |
Social Knowledge in Multiagent Systems | 211 |
Mařík M Pěchouček and O Štěpánková | 246 |
Kazakov and D Kudenko | 268 |
Exercises in Systems Modularity | 281 |
J Kelemen | 299 |
Multiagent Coordination and Control Using Stigmery Applied | 317 |
Specialised Agent Applications | 365 |
AgentBased Modelling of Ecosystems for Sustainable Resource Management | 383 |
J Doran | 401 |
B Nebel | 414 |
Author Index | 437 |
Wirsing | 73 |
Contributed Papers | 116 |
Bert R Echahed | 132 |
Bidoit R Hennicker | 153 |
Broy | 170 |
Cerioli | 188 |
G Denker | 203 |
H D Ehrich A Sernadas | 217 |
H Ehrig M Löwe F Orejas | 236 |
Fernández J P Jouannaud | 255 |
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多く使われている語句
abstract actions Agent Communication Language agent-based agents algorithm application approach architecture Artificial Intelligence axioms basic behavior called camera clause Color commonsense knowledge communication components Computer Science concept constraints Construction cooperation coordination defined Definition denotes distributed domain dynamic entailment systems environment equational logic equations example FIPA formal framework function goal grammar holon implemented infrastructure ingredient instantiated interactions interethnic interoperability knowledge base KQML learning light logic Machine Learning meta-agent module Multi-Agent Systems MULTISET negotiation node Object ontology operations organizations Pangu parameters parsing planning plot predicate problem Proc production programming proof calculi protocols query reinforcement learning relation representation resource RETSINA rewriting robots role rules semantics sentence Sequence Snow White software agents solving specification languages Springer-Verlag statement story strategy structure SWAN syntax Target task Teamcore techniques theory tion tree values variables