Solving distributed constraint optimization problems using logic programming
| Autor: | Enrico Pontelli, William Yeoh, Tiep Le, Tran Cao Son |
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| Rok vydání: | 2017 |
| Předmět: |
FOS: Computer and information sciences
Concurrent constraint logic programming Mathematical optimization Computer Science - Artificial Intelligence Computer science 0102 computer and information sciences 02 engineering and technology ComputingMethodologies_ARTIFICIALINTELLIGENCE 01 natural sciences Theoretical Computer Science Answer set programming Artificial Intelligence Constraint logic programming 0202 electrical engineering electronic engineering information engineering Constraint programming Reactive programming Computer Science - Multiagent Systems Logic programming General Medicine Constraint satisfaction Inductive programming Artificial Intelligence (cs.AI) Computational Theory and Mathematics 010201 computation theory & mathematics Hardware and Architecture 020201 artificial intelligence & image processing Software Multiagent Systems (cs.MA) |
| Zdroj: | Scopus-Elsevier |
| ISSN: | 1475-3081 1471-0684 |
| DOI: | 10.1017/s147106841700014x |
| Popis: | 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. Under consideration in Theory and Practice of Logic Programming (TPLP). Under consideration in Theory and Practice of Logic Programming (TPLP) |
| Databáze: | OpenAIRE |
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