Distributed Gibbs: A linear-space sampling-based DCOP algorithm

• Main Authors: NGUYEN, Duc Thien, YEOH, William, LAU, Hoong Chuin, ZIVAN, Roie
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2019
• Subjects: Constrained optimization; Ducts; Multi agent systems; Confidence bounds; Distributed constraint optimizations; Large problems; Memory requirements; Multi-agent coordinations; Resource allocation problem; Sampling-based; Sampling-based algorithms; Problem solving; Artificial Intelligence and Robotics; Theory and Algorithms
• Online Access: https://ink.library.smu.edu.sg/sis_research/4348; https://ink.library.smu.edu.sg/context/sis_research/article/5351/viewcontent/Distributed_Gibbs_A_linearspace_samplingbased_DCOP_algorithm2019Journal_of_Artificial_Intelligence_ResearchOpen_Access__1_.pdf
• Institution: Singapore Management University

Researchers have used distributed constraint optimization problems (DCOPs) to model various multi-agent coordination and resource allocation problems. Very recently, Ottens et al. proposed a promising new approach to solve DCOPs that is based on confidence bounds via their Distributed UCT (DUCT) sam...