@inproceedings{5eac70dd98f44040bde1bd0b2ca706fa,
title = "Branch-and-bound heuristics for incomplete DCOPs",
abstract = "The Incomplete Distributed Constraint Optimization Problem (IDCOP) extends the distributed constraint optimization problem, where constraint costs are allowed to be unspecified. A distributed variant of the Synchronous Branch-and-Bound (SyncBB) search algorithm has been proposed to solve I-DCOPs, where unspecified constraint costs are elicited during its execution. In this paper, we propose two heuristics that can be used in conjunction with SyncBB to solve I-DCOPs. Our proposed heuristics speed up the algorithm by pruning those parts of the search space whose solution quality is sub-optimal. Thus, our model and heuristics extend the state of the art in distributed constraint reasoning to better model and solve distributed agent-based applications with user preferences.",
keywords = "DCOPs, Heuristics, Multi-Agent Problems, Preference Elicitation",
author = "Tabakhi, {Atena M.} and Yuanming Xiao and William Yeoh and Roie Zivan",
note = "Publisher Copyright: {\textcopyright} 2021 International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). All rights reserved.; 20th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2021 ; Conference date: 03-05-2021 Through 07-05-2021",
year = "2021",
month = jan,
day = "1",
language = "American English",
series = "Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS",
pages = "1665--1667",
booktitle = "20th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2021",
}