TY - GEN
T1 - Resource Constrained Distributed Constraint Optimization using resource constraint free pseudo-tree
AU - Matsui, Toshihiro
AU - Silaghi, Marius
AU - Hirayama, Katsutoshi
AU - Yokoo, Makoto
AU - Matsuo, Hirohsi
PY - 2008
Y1 - 2008
N2 - The Distributed Constraint Optimization Problem (DCOP) is a fundamental formalism for multi-agent cooperation. A dedicated framework called Resource Constrained DCOP (RCDCOP) has recently been proposed. RCDCOP models objective functions and resource constraints separately. A resource constraint is an nary constraint that represents the limit on the number of resources of a given type available to agents. Previous research addressing RCDCOPs employs the Adopt algorithm, which is a basic solver for DCOPs. In this paper we propose another version of the Adopt algorithm for RCDCOP using a pseudo-tree that is generated ignoring resource constraints. The key ideas of our work are as follows: (i) The pseudo-tree is generated ignoring resource constraints, (ii) Virtual variables are introduced, representing the usage of resources. These virtual variables are used to share resources among subtrees. These ideas are used to extend Adopt. The proposed method reduces the previous limitations in the construction of RCDCOP pseudo-trees. The efficiency of our technique depends on the class of problems being considered, and we describe the obtained experimental results.
AB - The Distributed Constraint Optimization Problem (DCOP) is a fundamental formalism for multi-agent cooperation. A dedicated framework called Resource Constrained DCOP (RCDCOP) has recently been proposed. RCDCOP models objective functions and resource constraints separately. A resource constraint is an nary constraint that represents the limit on the number of resources of a given type available to agents. Previous research addressing RCDCOPs employs the Adopt algorithm, which is a basic solver for DCOPs. In this paper we propose another version of the Adopt algorithm for RCDCOP using a pseudo-tree that is generated ignoring resource constraints. The key ideas of our work are as follows: (i) The pseudo-tree is generated ignoring resource constraints, (ii) Virtual variables are introduced, representing the usage of resources. These virtual variables are used to share resources among subtrees. These ideas are used to extend Adopt. The proposed method reduces the previous limitations in the construction of RCDCOP pseudo-trees. The efficiency of our technique depends on the class of problems being considered, and we describe the obtained experimental results.
UR - https://www.scopus.com/pages/publications/84899961656
UR - https://www.scopus.com/pages/publications/84899961656#tab=citedBy
M3 - Conference contribution
AN - SCOPUS:84899961656
SN - 9781605604701
T3 - Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS
SP - 1373
EP - 1376
BT - 7th International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS 2008
PB - International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
T2 - 7th International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS 2008
Y2 - 12 May 2008 through 16 May 2008
ER -