Reference
J. Fransman, J. Sijs, H. Dol, E. Theunissen, and B. De Schutter, "Bayesian-DPOP
for continuous distributed constraint optimization problems,"
Proceedings of the 18th International Conference on Autonomous
Agents and MultiAgent Systems (AAMAS'19), Montreal, Canada, pp.
1961-1963, May 2019.
Abstract
In this work, the novel algorithm Bayesian Dynamic Programming Optimization
Procedure (B-DPOP) is presented to solve multi-agent problems within the
Distributed Constraint Optimization Problem framework. The Bayesian
optimization framework is used to prove convergence to the global optimum of
the B-DPOP algorithm for Lipschitz-continuous objective functions. The proposed
algorithm is assessed based on the benchmark problem known as dynamic sensor
placement. Results show increased performance over related algorithms in terms
of sample-efficiency.
Publisher page
Downloads
BibTeX
@inproceedings{FraSij:19-020,
author = {Fransman, Jeroen and Sijs, Joris and Dol, Henry and Theunissen,
Erik and De Schutter, Bart},
title = {Bayesian-{DPOP} for Continuous Distributed Constraint
Optimization Problems},
booktitle = {Proceedings of the 18th International Conference on Autonomous
Agents and MultiAgent Systems (AAMAS'19)},
address = {Montreal, Canada},
pages = {1961--1963},
month = may,
year = {2019}
}