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BD-ADOPT: a hybrid DCOP algorithm with best-first and depth-first search strategies

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Abstract

Distributed Constraint Optimization Problem (DCOP) is a promising framework for modeling a wide variety of multi-agent coordination problems. Best-First search (BFS) and Depth-First search (DFS) are two main search strategies used for search-based complete DCOP algorithms. Unfortunately, BFS often has to deal with a large number of solution reconstructions whereas DFS is unable to promptly prune sub-optimal branch. However, their weaknesses will be remedied if the two search strategies are combined based on agents’ positions in a pseudo-tree. Therefore, a hybrid DCOP algorithm with the combination of BFS and DFS, called BD-ADOPT, is proposed, in which a layering boundary is introduced to divide all agents into BFS-based agents and DFS-based agents. Furthermore, this paper gives a rule to find a suitable layering boundary with a new strategy for the agents near the boundary to realize the seamless joint between BFS and DFS strategies. Detailed experimental results show that BD-ADOPT outperforms some famous search-based complete DCOP algorithms on the benchmark problems.

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Acknowledgements

This work is partly supported by the Fundamental Research Funds for the Central University of China (Project No.106112013 CDJZR180013), the Postdoctoral Science Foundation of Chongqing in China (Project No. Xm201324) and the Innovation Projects in Chongqing (Project No. CYS14018). We are also grateful to the reviewers of this article for their kind suggestions.

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Authors and Affiliations

  1. College of Computer Science, Chongqing University, Chongqing, 400044, China

    Ziyu Chen, Chen He & Zhen He

  2. College of Electrical Engineering, Chongqing University, Chongqing, 400044, China

    Minyou Chen

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  1. Ziyu Chen
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  2. Chen He
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  3. Zhen He
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  4. Minyou Chen
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Correspondence to Ziyu Chen.

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Chen, Z., He, C., He, Z. et al. BD-ADOPT: a hybrid DCOP algorithm with best-first and depth-first search strategies. Artif Intell Rev 50, 161–199 (2018). https://doi.org/10.1007/s10462-017-9540-z

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  • DOI: https://doi.org/10.1007/s10462-017-9540-z

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