Distributed constraint optimization for continuous mobile sensor coordination
conference paper
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 Opti- mization 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. © 2018 European Control Association (EUCA).
Topics
TNO Identifier
861665
ISBN
9783952426982
Publisher
Institute of Electrical and Electronics Engineers Inc.
Article nr.
8550486
Source title
2018 European Control Conference, ECC 2018, 16th European Control Conference, ECC 2018, 12 June 2018 through 15 June 2018
Pages
1100-1105
Files
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