Distributed Constraint Optimization Problems: Review and perspectives

• Published in: Expert systems with applications Vol. 41; no. 11; pp. 5139 - 5157
• Main Authors: Leite, Allan R., Enembreck, Fabrício, Barthès, Jean-Paul A.
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier Ltd 01.09.2014; Elsevier
• Subjects: Agents (artificial intelligence); Applied sciences; Artificial Intelligence; Autonomous agents; Complex systems; Computer Science; Computer science; control theory; systems; Computer systems and distributed systems. User interface; Distributed Constraint Optimization Problems; Evolution; Exact sciences and technology; Expert systems; Formalism; Intelligent agents; Multi-agent systems; Optimization; Software; Distributed Constraint Optimization Problems; Autonomous agents; Multi-agent systems; Autonomous system; Coordination; Complex system; Distributed system; Modeling; Intelligent agent; Constrained optimization; Problems; Multiagent system; Problem solving; Distributed Constraint Optimization; Artificial intelligence; Metamodel; distributed constraint optimization
• ISSN: 0957-4174; 1873-6793
• DOI: 10.1016/j.eswa.2014.02.039

•DCOP has emerged as an important formalism for coordination in multi-agent systems.•DCOP is capable to model a large class of complex real world problems naturally.•We present DCOP background and a review of the main algorithms.•We discuss about perspectives of DCOP research area. Intelligent agents is a research area of the Artificial Intelligence intensely studied since the 1980s. Multi-agent systems represent a powerful paradigm of analyzing, projecting, and developing complex systems. One of the main difficulties in modeling a multi-agent system is defining the coordination model, due to the autonomous behavior of the agents. Distributed Constraint Optimization Problems (DCOP) have emerged as one of most important formalisms for coordination and distributed problem solving in multi-agent systems and are capable of modeling a large class of real world problems naturally. This work aims to provide an overview and critical review of DCOP, addressing the most popular methods and techniques, the evolution and comparison of algorithms, and future perspectives on this promising research area.