TY - GEN
T1 - Embedding preference ordering for symmetric DCOP solvers on spanning trees
AU - Matsui, Toshihiro
AU - Silaghi, Marius
AU - Hirayama, Katsutoshi
AU - Yokoo, Makoto
AU - Matsuo, Hiroshi
PY - 2013
Y1 - 2013
N2 - The Max-Sum algorithm is a solution method for the Distributed Constraint Optimization Problem (DCOP) which is a fundamental problem in multiagent cooperation. Particularly, we focus on the case of Max-Sum on a spanning tree, where the algorithm is an exact solution method. In this case, all agents simultaneously compute globally optimal objective values as erootf nodes of the tree that represents the problem. On the other hand, a tiebreak is generally necessary in order to determine a unique optimal solution among the agents. While top-down post-processing is a well-known solution, one can prefer to design the solver as a bottom-up computation that is simply integrated to pre-processing. To address this issue, we investigate a technique that employs a preference ordering based on spanning trees for the optimization algorithms. With this technique, top-down processing to choose a unique optimal solution can be embedded into bottom-up optimization via small weight values for the preference ordering. We also evaluate an integrated algorithm that maintains both tree structures and quasi-optimal solutions using the bottom-up approaches.
AB - The Max-Sum algorithm is a solution method for the Distributed Constraint Optimization Problem (DCOP) which is a fundamental problem in multiagent cooperation. Particularly, we focus on the case of Max-Sum on a spanning tree, where the algorithm is an exact solution method. In this case, all agents simultaneously compute globally optimal objective values as erootf nodes of the tree that represents the problem. On the other hand, a tiebreak is generally necessary in order to determine a unique optimal solution among the agents. While top-down post-processing is a well-known solution, one can prefer to design the solver as a bottom-up computation that is simply integrated to pre-processing. To address this issue, we investigate a technique that employs a preference ordering based on spanning trees for the optimization algorithms. With this technique, top-down processing to choose a unique optimal solution can be embedded into bottom-up optimization via small weight values for the preference ordering. We also evaluate an integrated algorithm that maintains both tree structures and quasi-optimal solutions using the bottom-up approaches.
UR - http://www.scopus.com/inward/record.url?scp=84893068722&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84893068722&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-44927-7_14
DO - 10.1007/978-3-642-44927-7_14
M3 - Conference contribution
AN - SCOPUS:84893068722
SN - 9783642449260
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 197
EP - 212
BT - PRIMA 2013
T2 - 16th International Conference on Principles and Practice of Multi-Agent Systems, PRIMA 2013
Y2 - 1 December 2013 through 6 December 2013
ER -