By Frank van Harmelen (auth.), Matthias Klusch, Michael Rovatsos, Terry R. Payne (eds.)
This publication constitutes the refereed court cases of the tenth foreign Workshop on Cooperative info brokers, CIA 2006, held in Edinburgh, united kingdom in September 2006.
The 29 revised complete papers awarded including 4 invited papers have been conscientiously reviewed and chosen from fifty eight submissions. The papers are geared up in topical sections on team interplay, reasoning approximately software, the dynamics of agent established details provision, purposes, brokers and providers, studying, source and activity allocation, rational cooperation, verbal exchange and cooperation, and agent established grid computing.
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Extra resources for Cooperative Information Agents X: 10th International Workshop, CIA 2006 Edinburgh, UK, September 11-13, 2006 Proceedings
Voting in Cooperative Information Agent Scenarios: Use and Abuse 39 – Copeland: For each possible pair of candidates, simulate an election; a candidate wins such a pairwise election if more voters prefer it over the opponent. A candidate gets 1 point for each pairwise election it wins, and −1 for each pairwise election it loses. – Maximin: A candidate’s score in a pairwise election is the number of voters that prefer it over the opponent. The winner is the candidate whose minimum score over all pairwise elections is highest.
Doc 5. Bradshaw, J M, Dutfield, S, Benoit, P, and Woolley, J D. (1997) KAoS: Toward an industrial-strength open agent architecture. In Software Agents, AAAI Press/MIT Press, Cambridge, Massachusetts, editor J M Bradshaw. Pages 375-418. 6. , Shadbolt, N. and Tate, A. (2002) CoAKTinG: Collaborative Advanced Knowledge Technologies in the Grid, Proceedings of the Second Workshop on Advanced Collaborative Environments, Eleventh IEEE Int. Symposium on High Performance Distributed Computing (HPDC-11), July 24-26, 2002, Edinburgh, Scotland.
The type of work described in this paper has had an inﬂuence on political science and sociology. 3. An avid consumer of the results produced by other ﬁelds. The interdisciplinary nature of computer science is nowhere more evident than in the area of artiﬁcial intelligence (AI), and perhaps nowhere more evident in artiﬁcial intelligence than in its subarea of multiagent systems. MAS researchers for the last 20 years have eagerly derived inspiration from ﬁelds as diverse as biology, physics, sociology, economics, organization theory, and mathematics.
Cooperative Information Agents X: 10th International Workshop, CIA 2006 Edinburgh, UK, September 11-13, 2006 Proceedings by Frank van Harmelen (auth.), Matthias Klusch, Michael Rovatsos, Terry R. Payne (eds.)