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Coalitions Among Computationally Bounded Agents (1997)
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| Venue: | Artificial Intelligence |
| Citations: | 203 - 26 self |
BibTeX
@ARTICLE{Sandholm97coalitionsamong,
author = {Tuomas W. Sandholm and Victor R. Lesser},
title = {Coalitions Among Computationally Bounded Agents},
journal = {Artificial Intelligence},
year = {1997},
volume = {94},
pages = {99--137}
}
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Abstract
This paper analyzes coalitions among self-interested agents that need to solve combinatorial optimization problems to operate e ciently in the world. By colluding (coordinating their actions by solving a joint optimization prob-lem) the agents can sometimes save costs compared to operating individually. A model of bounded rationality is adopted where computation resources are costly. It is not worthwhile solving the problems optimally: solution quality is decision-theoretically traded o against computation cost. A normative, application- and protocol-independent theory of coalitions among bounded-rational agents is devised. The optimal coalition structure and its stability are signi cantly a ected by the agents ' algorithms ' performance pro les and the cost of computation. This relationship is rst analyzed theoretically. Then a domain classi cation including rational and bounded-rational agents is in-troduced. Experimental results are presented in vehicle routing with real data from ve dispatch centers. This problem is NP-complete and the instances are so large that|with current technology|any agent's rationality is bounded by computational complexity. 1
Keyphrases
bounded-rational agent optimal coalition structure computation resource self-interested agent experimental result bounded rationality computation cost performance pro le real data domain classi cation joint optimization prob-lem ve dispatch center computational complexity solution quality protocol-independent theory combinatorial optimization problem current technology
