2014/05/07 by Tiep Le, Le, Tiep, Enrico Pontelli +5
Computer Science · #68-06 #Artificial Intelligence (cs.AI) #Constraint Satisfaction and Optimization #Data Management and Algorithms #FOS: Computer and information sciences #Logic, Reasoning, and Knowledge #Multiagent Systems (cs.MA)
paper · pdf · doi:10.48550/arxiv.1405.1734
openalex publication_date 2014/05/07 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The field of Distributed Constraint Optimization Problems (DCOPs) has gained momentum, thanks to its suitability in capturing complex problems (e.g., multi-agent coordination and resource allocation problems) that are naturally distributed and cannot be realistically addressed in a centralized manner. The state of the art in solving DCOPs relies on the use of ad-hoc infrastructures and ad-hoc constraint solving procedures. This paper investigates an infrastructure for solving DCOPs that is completely built on logic programming technologies. In particular, the paper explores the use of a general constraint solver (a constraint logic programming system in this context) to handle the agent-level constraint solving. The preliminary experiments show that logic programming provides benefits over a state-of-the-art DCOP system, in terms of performance and scalability, opening the doors to the use of more advanced technology (e.g., search strategies and complex constraints) for solving DCOPs.