Incremental DCOP Search Algorithms for Solving Dynamic DCOP Problems

Distributed constraint optimization (DCOP) problems are well-suited for modeling multi-agent coordination problems. However, it only models static problems, which do not change over time. Consequently, researchers have introduced the Dynamic DCOP (DDCOP) model to model dynamic problems. In this pape...

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Bibliographic Details
Main Authors: YEOH, William, Pradeep VARAKANTHAM, SUN, Xiaoxun, KOENIG, Sven
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2015
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Online Access:https://ink.library.smu.edu.sg/sis_research/3153
https://ink.library.smu.edu.sg/context/sis_research/article/4153/viewcontent/P_ID_52426_DDCOP.pdf
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Institution: Singapore Management University
Language: English
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Summary:Distributed constraint optimization (DCOP) problems are well-suited for modeling multi-agent coordination problems. However, it only models static problems, which do not change over time. Consequently, researchers have introduced the Dynamic DCOP (DDCOP) model to model dynamic problems. In this paper, we make two key contributions: (a) a procedure to reason with the incremental changes in DDCOPs and (b) an incremental pseudo-tree construction algorithm that can be used by DCOP algorithms such as any-space ADOPT and any-space BnB-ADOPT to solve DDCOPs. Due to the incremental reasoning employed, our experimental results show that any-space ADOPT and any-space BnB-ADOPT are up to 42% and 38% faster, respectively, with the incremental procedure and the incremental pseudo-tree reconstruction algorithm than without them.