Distributed Breakout: Beyond Satisfaction
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence. Pages 447-452.
Abstract
The Distributed Breakout Algorithm (DBA) is a local search algorithm that was originally designed to solve DisCSPs and DisMaxCSPs. Extending it to general-valued DCOPs requires three design choices: manner of modifying base costs (multiplicative weights or additive penalties); definition of constraint violation (non-zero cost, non-minimum cost, and maximum cost); and scope of modifying cost tables during breakout (entry, row, column, or table). We propose Generalized DBA (GDBA) to span the 24 combinations in the three dimensions. In our theoretical analysis we prove that some variants of GDBA are equivalent for certain problems, and prove that other variants may find suboptimal solutions even on tree topologies where DBA is complete. Our extensive empirical evaluation on various benchmarks shows that in practice, GDBA is capable of finding solutions of equal or significantly lower cost than alternative heuristic approaches (including DSA).
@inproceedings{ijcai2016p70,
title = {Distributed Breakout: Beyond Satisfaction},
author = {Okamoto, Steven and Zivan, Roie and Nahon, Aviv},
booktitle = {Proceedings of the Twenty-Fifth International Joint Conference on
Artificial Intelligence, {IJCAI-16}},
publisher = {AAAI Press / International Joint Conferences on Artificial Intelligence},
editor = {Subbarao Kambhampati},
pages = {447--452},
year = {2016},
month = {7},
url = {https://ijcai.org/proceedings/2016/70},
}
TY - CPAPER TI - Distributed Breakout: Beyond Satisfaction AU - Okamoto, Steven AU - Zivan, Roie AU - Nahon, Aviv T2 - Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, IJCAI-16 PB - AAAI Press / International Joint Conferences on Artificial Intelligence PY - 2016 SP - 447 EP - 452 UR - https://ijcai.org/proceedings/2016/70 ER -Copied
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