2 research outputs found
Solving Distributed Constraint Optimization Problems Using Logic Programming
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).Comment: Under consideration in Theory and Practice of Logic Programming
(TPLP
Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence A Logical Formulation for Negotiation Among Dishonest Agents β
The paper introduces a logical framework for negotiation among dishonest agents. The framework relies on the use of abductive logic programming as a knowledge representation language for agents to deal with incomplete information and preferences. The paper shows how intentionally false or inaccurate information of agents could be encoded in the agents β knowledge bases. Such disinformation can be effectively used in the process of negotiation to have desired outcomes by agents. The negotiation processes are formulated under the answer set semantics of abductive logic programming and enable the exploration of various strategies that agents can employ in their negotiation.