Incomplete Distributed Constraint Optimization Problems: Model, Algorithms, and Heuristics. Model, Algorithms, and Heuristics

Atena M. Tabakhi, William Yeoh, Roie Zivan

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

Abstract

The Distributed Constraint Optimization Problem (DCOP) formulation is a powerful tool to model cooperative multi-agent problems, especially when they are sparsely constrained with one another. A key assumption in this model is that all constraints are fully specified or known a priori, which may not hold in applications where constraints encode preferences of human users. In this paper, we extend the model to Incomplete DCOPs (I-DCOPs), where some constraints can be partially specified. User preferences for these partially-specified constraints can be elicited during the execution of I-DCOP algorithms, but they incur some elicitation costs. Additionally, we extend SyncBB, a complete DCOP algorithm, and ALS-MGM, an incomplete DCOP algorithm, to solve I-DCOPs. We also propose parameterized heuristics that those algorithms can utilize to trade off solution quality for faster runtime and fewer elicitation. They also provide theoretical quality guarantees when used by SyncBB when elicitations are free. Our model and heuristics thus extend the state-of-the-art in distributed constraint reasoning to better model and solve distributed agent-based applications with user preferences.

Original languageEnglish
Title of host publicationInternational Conference on Distributed Artificial Intelligence
EditorsJie Chen, Jérôme Lang, Christopher Amato, Dengji Zhao
PublisherSpringer Science and Business Media Deutschland GmbH
Pages64-78
Number of pages15
ISBN (Electronic)978-3-030-94662-3
ISBN (Print)9783030946616
DOIs
StatePublished - 1 Jan 2022
Event3rd International Conference on Distributed Artificial Intelligence, DAI 2021 - Shanghai, China
Duration: 17 Dec 202118 Dec 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13170 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference3rd International Conference on Distributed Artificial Intelligence, DAI 2021
Country/TerritoryChina
CityShanghai
Period17/12/2118/12/21

Keywords

  • Distributed constraint optimization problems
  • Distributed problem solving
  • Multi-agent problems
  • Preference elicitation

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

Fingerprint

Dive into the research topics of 'Incomplete Distributed Constraint Optimization Problems: Model, Algorithms, and Heuristics. Model, Algorithms, and Heuristics'. Together they form a unique fingerprint.

Cite this