In spite of the fantastic efforts in developing efficient implementations, there are important application domains that are beyond the computational reach of existing sequential systems. In this research, we explore the use of parallelism as an avenue to expand efficiency and applicability of LPNMR systems. We explore the major issues involved in the automatic exploitation of parallelism from the execution models of LPNMR systems. We describe orthogonal techniques to parallelize the computational models of Answer Set Programming, and investigate a wide range of sharing strategies and dynamic schedulers. We demonstrate the effectiveness of the proposed techniques in a prototype implementation.
We describe the design of ASP-PROLOG along with its implementation, realized using CIAO Prolog and Smodels.
In addition, we introduce the notion of
off-line justification for Answer Set Programming. Justifications
provide a graph-based explanation of the truth value of an atom
w.r.t. a given answer set. The notion of justification accounts for the
specifics of answer set semantics. The thesis extends also this notion
to provide justification of atoms during the computation of an
answer set (on-line justification), and presents an integration
of on-line justifications within the computation model of
Smodels. Off-line and on-line justifications provide useful tools
to enhance understanding of ASP, and they offer a basic data structure
to support methodologies and tools for debugging answer set programs.
An implementation has been developed in ASP-PROLOG.