A comparative analysis and improvement of MaxSAT encodings for coalition structure generation under MC-nets

Author:

Liao Xiaojuan1,Koshimura Miyuki2

Affiliation:

1. School of Cyberspace Security, Chengdu University of Technology, Chengdu, Sichuan, China

2. Faculty of Information Science and Electrical Engineering, Kyushu University, Fukuoka, Fukuoka, Japan

Abstract

Abstract Coalition structure generation (CSG) is one of the main research issues in the use of coalitional games in multiagent systems and weighted partial MaxSAT (WPM) encodings, i.e. rule relation-based WPM (RWPM) and agent relation-based WPM (AWPM), which are efficient for solving the CSG problem. Existing studies show that AWPM surpasses RWPM since it achieves more compact encoding; it generates fewer variables and clauses than RWPM. However, in this paper, we focus on a special case in which the two encodings generate identical numbers of variables and clauses. Experiments show that RWPM surprisingly has a dominant advantage over AWPM, which aroused our interest. We exploit the deep-rooted reason and find that it is the redundancy when encoding transitive laws in RWPM that leads to this situation. Finally, we remove redundant clauses for transitive laws in RWPM and develop an improved RWPM with refined transitive laws to solve the CSG problem. Experiments demonstrate that refined encoding is more compact and efficient than previous WPM encodings.

Funder

National Natural Science Foundation of China

Ministry of Education in China Project of Humanities and Social Sciences

JSPS KAKENHI

Publisher

Oxford University Press (OUP)

Subject

Logic,Hardware and Architecture,Arts and Humanities (miscellaneous),Software,Theoretical Computer Science

Reference11 articles.

1. Coalition structure generation with worst case guarantees;Sandholm,1999

2. Marginal contribution nets: a compact representation scheme for coalitional games;Ieong,2005

3. A logic-based representation for coalitional games with externalities;Michalak,2010

4. Coalition structure generation utilizing compact characteristic function representation;Ohta,2009

5. Handling negative value rules in MC-net-based coalition structure generation;Ueda,2012

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