Solving Distributed Constraint Optimization Problems Using Logic Programming
This provides a more efficient and scalable solution for multi-agent systems modeled as DCOPs, though it is incremental as it builds on existing DCOP methods.
The paper tackles Distributed Constraint Optimization Problems (DCOPs) by using Answer Set Programming (ASP) to formulate them as logic programs and introduces ASP-DPOP, a new algorithm that is up to two orders of magnitude faster than DPOP and solves problems DPOP cannot due to memory limitations.
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).