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A Distributed Approach to Summarizing Spaces of Multiagent Schedules

James C. Boerkoel, Edmund H. Durfee

2021Proceedings of the AAAI Conference on Artificial Intelligence14 citationsDOIOpen Access PDF

Abstract

We introduce the Multiagent Disjunctive Temporal Problem (MaDTP), a new distributed formulation of the widely-adopted Disjunctive Temporal Problem (DTP) representation. An agent that generates a summary of all viable schedules, rather than a single schedule, can be more useful in dynamic environments. We show how a (Ma)DTP with the properties of minimality and decomposability provides a particularly efficacious solution space summary.However, in the multiagent case, these properties sacrifice an agent's strategic interests while incurring significant computational overhead. We introduce a new property called local decomposability that exploits loose-coupling between agents' problems, protects strategic interests, and supports typical queries. We provide and evaluate a new distributed algorithm that summarizes agents' solution spaces in significantly less time and space by using local, rather than full, decomposability.

Topics & Concepts

Computer scienceScheduleExploitOverhead (engineering)Distributed computingProperty (philosophy)Representation (politics)Multi-agent systemSpace (punctuation)Theoretical computer scienceMathematical optimizationArtificial intelligenceMathematicsComputer securityProgramming languagePhilosophyPoliticsLawEpistemologyPolitical scienceOperating systemConstraint Satisfaction and OptimizationScheduling and Optimization AlgorithmsData Management and Algorithms
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