Neural regret-matching for distributed constraint optimization problems

• Main Authors: DENG, Yanchen, YU, Runshen, WANG, Xinrun, AN, Bo
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2021
• Subjects: Agent-based and Multi-agent Systems; Coordination and Cooperation; Constraints and SAT: Constraint OptimizationConstraints and SAT; Distributed Constraints; Artificial Intelligence and Robotics; Theory and Algorithms
• Online Access: https://ink.library.smu.edu.sg/sis_research/9142; https://ink.library.smu.edu.sg/context/sis_research/article/10145/viewcontent/Neural_Regret_Matching_pvoa.pdf
• Institution: Singapore Management University

Distributed constraint optimization problems (DCOPs) are a powerful model for multi-agent coordination and optimization, where information and controls are distributed among multiple agents by nature. Sampling-based algorithms are important incomplete techniques for solving medium-scale DCOPs. Howev...