Partially cooperative multi-agent periodic indivisible resource allocation

Yuval Gabai Shlosberg, Roie Zivan

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Asymmetric distributed constraint optimization problems (ADCOPs) in which agents are partially cooperative, is a model for representing multi-agent optimization problems in which agents, are willing to cooperate in order to achieve a global goal, as long as some minimal threshold on their personal utility is satisfied. We contribute by: 1) extending the ADCOP model to represent resource allocation problems in which indivisible resources are periodically allocated, e.g., meeting rooms, operating rooms, etc. 2) adjusting partially cooperative local search algorithms to solve problems represented by the extended model. 3) presenting an implementation of a realistic problem that is represented by the proposed model, and empirical evidence of the compatibility of partially cooperative algorithms for this scenario.

Original languageEnglish
Title of host publication20th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2021
PublisherInternational Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
Pages1486-1488
Number of pages3
ISBN (Electronic)9781713832621
StatePublished - 1 Jan 2021
Event20th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2021 - Virtual, Online
Duration: 3 May 20217 May 2021

Publication series

NameProceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS
Volume3
ISSN (Print)1548-8403
ISSN (Electronic)1558-2914

Conference

Conference20th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2021
CityVirtual, Online
Period3/05/217/05/21

Keywords

  • Distributed Constraint Optimization
  • Distributed Local Search
  • Partial Cooperation

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software
  • Control and Systems Engineering

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