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Benchmarking hybrid algorithms for distributed constraint optimisation games

Journal Article OriginalPaper Artificial Intelligence ยท Multi-Agent Systems

Abstract

Abstract In this paper, we consider algorithms for distributed constraint optimisation problems (DCOPs). Using a potential game characterisation of DCOPs, we decompose eight DCOP algorithms, taken from the game theory and computer science literatures, into their salient components. We then use these components to construct three novel hybrid algorithms. Finally, we empirical evaluate all eleven algorithms, in terms of solution quality, timeliness and communication resources used, in a series of graph colouring experiments. Our experimental results show the existence of several performance trade-offs (such as quick convergence to a solution, but with a cost of high communication needs), which may be exploited by a system designer to tailor a DCOP algorithm to suit their mix of requirements.

Authors

Keywords

  • Distributed constraint optimisation
  • Potential games

Context

Venue
Autonomous Agents and Multi-Agent Systems
Archive span
2005-2026
Indexed papers
940
Paper id
967674041611069876
v2026.09.13