Distributed constraint optimization for continuous mobile sensor coordination


Reference:
J. Fransman, J. Sijs, H. Dol, E. Theunissen, and B. De Schutter, "Distributed constraint optimization for continuous mobile sensor coordination," Proceedings of the 2018 European Control Conference, Limassol, Cyprus, pp. 1100-1105, June 2018.

Abstract:
DCOP (Distributed Constraint Optimization Problem) is a framework for representing distributed multi-agent problems. However, it only allows discrete values for the decision variables, which limits its application for real-world problems. In this paper, an extension of DCOP is investigated to handle variables with continuous domains. Additionally, an iterative any-time algorithm Compression-DPOP (C-DPOP) is presented that is based on the Distributed Pseudo-tree Optimization Procedure (DPOP). C-DPOP iteratively samples the search space in order to handle problems that are restricted by time and memory limitations. The performance of the algorithm is examined through a mobile sensor coordination problem. The proposed algorithm outperforms DPOP with uniform sampling regarding both resource requirement and performance.


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Bibtex entry:

@inproceedings{FraSij:18-014,
        author={J. Fransman and J. Sijs and H. Dol and E. Theunissen and B. {D}e Schutter},
        title={Distributed constraint optimization for continuous mobile sensor coordination},
        booktitle={Proceedings of the 2018 European Control Conference},
        address={Limassol, Cyprus},
        pages={1100--1105},
        month=jun,
        year={2018}
        }



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