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Distributed algorithms for solving the multiagent temporal decoupling problem

By James C. Boerkoel and Edmund H. Durfee

Abstract

Scheduling agents can use the Multiagent Simple Temporal Problem (MaSTP) formulation to efficiently find and represent the complete set of alternative consistent joint schedules in a distributed and privacy-maintaining manner. However, continually revising this set of consistent joint schedules as new constraints arise may not be a viable option in environments where communication is uncertain, costly, or otherwise problematic. As an alternative, agents can find and represent a temporal decoupling in terms of locally independent sets of consistent schedules that, when combined, form a set of consistent joint schedules. Unlike current algorithms for calculating a temporal decoupling that require centralization of the problem representation, in this paper we present a new, provably correct, distributed algorithm for calculating a temporal decoupling. We prove that this algorithm has the same theoretical computational complexity as current state-of-the-art MaSTP solution algorithms, and empirically demonstrate that it is more efficient in practice. We also introduce and perform an empirical cost/benefit analysis of new techniques and heuristics for selecting a maximally flexible temporal decoupling

Topics: Categories and Subject Descriptors I.2.11 [Artificial Intelligence, Distributed Artificial Intelligence General Terms Algorithms, Experimentation, Theory Keywords Multiagent Scheduling, Temporal Decoupling Problem
Year: 2011
OAI identifier: oai:CiteSeerX.psu:10.1.1.309.7869
Provided by: CiteSeerX
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