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Speeding up distributed pseudo-tree optimization procedures with cross edge consistency to solve DCOPs

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Abstract

The Distributed Pseudo-tree Optimization Procedure (DPOP) is a well-known message passing algorithm that provides optimal solutions to Distributed Constraint Optimization Problems (DCOPs) in cooperative multi-agent systems. However, the traditional DCOP formulation does not consider constraints that must be satisfied (hard constraints), rather it concentrates only on constraints that place no restriction on satisfaction (soft constraints). This is a serious shortcoming as many real-world applications involve both types of constraints. Traditional DPOP algorithms are not able to benefit from the existence of hard constraints, where an additional calculation is required to handle such constraints. This results in longer runtimes. Thus scalability remains an issue. Additionally, in the standard DPOP, the agents are arranged as a Depth First Search (DFS) pseudo-tree, but recent work has shown that the construction of pseudo-trees in this way often leads to chain-like communication structures that greatly impair the algorithm’s performance. To address these issues, we develop an algorithm that speeds up the DPOP algorithm by reducing the size of the messages exchanged and increases parallelism in the pseudo tree. For this purpose, initially, we improve the path for exchanging messages. Next, we introduce a new form of constraint propagation, which we call cross-edge consistency. Our theoretical evaluation shows that our proposed algorithm is complete and correct. In empirical evaluations, our algorithm achieves a significant reduction in the runtime, ranging from 4% to 96%, compared to the state-of-the-art.

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Notes

  1. Cross-edge Consistency is a new form of consistency introduced in this paper for pruning out those possible values for the variables in a DCOP which cannot possibly be part of a consistent solution.

  2. Throughout this paper, we consider agents and variables as interchangeable.

  3. A communication structure is a path along which DCOP message passing takes place.

  4. The work presented in [2] has shown that DFS traversal often leads to low-quality chain-like pseudo-trees with poor parallelism.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, University of Dhaka, Dhaka, Bangladesh

    Mashrur Rashik, Md. Musfiqur Rahman, Md. Mosaddek Khan & Md. Mamun-or-Rashid

  2. School of Electronics and Computer Science, University of Southampton, Southampton, UK

    Long Tran-Thanh

  3. Departments of Computing and Electrical and Electronic Engineering, Imperial College London, London, UK

    Nicholas R. Jennings

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  1. Mashrur Rashik
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  2. Md. Musfiqur Rahman
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  4. Md. Mamun-or-Rashid
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  5. Long Tran-Thanh
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  6. Nicholas R. Jennings
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Correspondence to Mashrur Rashik.

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Rashik, M., Rahman, M.M., Khan, M.M. et al. Speeding up distributed pseudo-tree optimization procedures with cross edge consistency to solve DCOPs. Appl Intell 51, 1733–1746 (2021). https://doi.org/10.1007/s10489-020-01860-8

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