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Solving distributed constraint optimization problems using logic programming*

Published online by Cambridge University Press:  27 June 2017

TIEP LE
Affiliation:
Computer Science Department, New Mexico State University, Las Cruces, NM 88001, USA (e-mails: tile@cs.nmsu.edu, tson@cs.nmsu.edu, epontell@cs.nmsu.edu, wyeoh@cs.nmsu.edu)
TRAN CAO SON
Affiliation:
Computer Science Department, New Mexico State University, Las Cruces, NM 88001, USA (e-mails: tile@cs.nmsu.edu, tson@cs.nmsu.edu, epontell@cs.nmsu.edu, wyeoh@cs.nmsu.edu)
ENRICO PONTELLI
Affiliation:
Computer Science Department, New Mexico State University, Las Cruces, NM 88001, USA (e-mails: tile@cs.nmsu.edu, tson@cs.nmsu.edu, epontell@cs.nmsu.edu, wyeoh@cs.nmsu.edu)
WILLIAM YEOH
Affiliation:
Computer Science Department, New Mexico State University, Las Cruces, NM 88001, USA (e-mails: tile@cs.nmsu.edu, tson@cs.nmsu.edu, epontell@cs.nmsu.edu, wyeoh@cs.nmsu.edu)

Abstract

This paper explores the use of Answer Set Programming (ASP) in solving Distributed Constraint Optimization Problems (DCOPs). The paper provides the following novel contributions: (1) it shows how one can formulate DCOPs as logic programs; (2) it introduces ASP-DPOP, the first DCOP algorithm that is based on logic programming; (3) it experimentally shows that ASP-DPOP can be up to two orders of magnitude faster than DPOP (its imperative programming counterpart) as well as solve some problems that DPOP fails to solve, due to memory limitations; and (4) it demonstrates the applicability of ASP in a wide array of multi-agent problems currently modeled as DCOPs.

Information

Type
Regular Papers
Copyright
Copyright © Cambridge University Press 2017 

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