ACLP: Flexible Solutions to Complex Problems

In this paper we present a new system for non-monotonic reasoning performed using abduction. The system, called ACLP, is a programming language based on the framework of Abductive and Constraint Logic Programming (ACLP) which integrates abduction and constraint solving in Logic Programming. It is build on top of the ECLiPSe language for Constraint Logic Programming (CLP) interfacing (and exploiting) appropriately the non-monotonic reasoning of abduction with the specialized constraint solving of the CLP language. ACLP is intended as a programming language that extends the underlying CLP language in which using NMR (in this case abduction) together with constraint solving it is possible to develop exible solutions that are computationally viable in the real-life domain. We present the basic theory of ACLP that underlies the system, the main features of the ACLP language and how it can be used when developing applications. We then report on some experiments performed in order to test the cost of the use of the ACLP system as compared with the direct use of the (lower level) constraint solving framework of CLP on which this is build. These experiments provide evidence that the non-monotonic framework of ACLP does not compromise signiicantly the computational eeciency of the solutions thus connrming the computational viability of the framework for the development of exible solutions to real-life applications.