Benjamin Kaufmann

Potassco: The Potsdam Answer Set Solving Collection

This paper gives an overview of the open source project Potassco, the Potsdam Answer Set Solving Collection, bundling tools for Answer Set Programming developed at the University of Potsdam.

Clasp: a conflict-driven answer set solver

We describe the conflict-driven answer set solver clasp, which is based on concepts from constraint processing (CSP) and satisfiability checking (SAT). We detail its system architecture and major features, and provide a systematic empirical evaluation of its features.

Answer Set Solving in Practice

Answer Set Programming (ASP) is a declarative problem solving approach, initially tailored to modeling problems in the area of Knowledge Representation and Reasoning (KRR). More recently, its attractive combination of a rich yet simple modeling language with high-performance solving capacities has sparked interest in many other areas even beyond KRR. This book presents a practical introduction to ASP, aiming at using ASP languages and systems for solving application problems. Starting from the essential formal foundations, it introduces ASPs solving technology, modeling language and methodology, while illustrating the overall solving process by practical examples. Table of Contents: List of Figures / List of Tables / Motivation / Introduction / Basic modeling / Grounding / Characterizations / Solving / Systems / Advanced modeling / Conclusions

Conflict-driven answer set solving: From theory to practice

We introduce an approach to computing answer sets of logic programs, based on concepts successfully applied in Satisfiability (SAT) checking. The idea is to view inferences in Answer Set Programming (ASP) as unit propagation on nogoods. This provides us with a uniform constraint-based framework capturing diverse inferences encountered in ASP solving. Moreover, our approach allows us to apply advanced solving techniques from the area of SAT. As a result, we present the first full-fledged algorithmic framework for native conflict-driven ASP solving. Our approach is implemented in the ASP solver clasp that has demonstrated its competitiveness and versatility by winning first places at various solver contests.

Engineering an Incremental ASP Solver

Many real-world applications, like planning or model checking, comprise a parameter reflecting the size of a solution. In a propositional formalism like Answer Set Programming (ASP), such problems can only be dealt with in a bounded way, considering one problem instance after another by gradually increasing the bound on the solution size. We thus propose an incremental approach to both grounding and solving in ASP. Our goal is to avoid redundancy by gradually processing the extensions to a problem rather than repeatedly re-processing the entire (extended) problem. We start by furnishing a formal framework capturing our incremental approach in terms of module theory. In turn, we take advantage of this framework for guiding the successive treatment of program slices during grounding and solving. Finally, we describe the first integrated incremental ASP system, iclingo , and provide an experimental evaluation.

The Conflict-Driven Answer Set Solver clasp: Progress Report

We summarize the salient features of the current version of the answer set solver clasp , focusing on the progress made since version RC4 of clasp . Apart from enhanced preprocessing and search-supporting techniques, a particular emphasis lies on advanced reasoning modes, such as cautious and brave reasoning, optimization, solution projection, and incremental solving.

A portfolio solver for answer set programming: preliminary report

We propose a portfolio-based solving approach to Answer Set Programming (ASP). Our approach is homogeneous in considering several configurations of the ASP solver clasp. The selection among the configurations is realized via Support Vector Regression. The resulting portfolio-based solver claspfolio regularly outperforms clasps default configuration as well as manual tuning.

Solution Enumeration for Projected Boolean Search Problems

Many real-world problems require the enumeration of all solutions of combinatorial search problems, even though this is often infeasible in practice. However, not always all parts of a solution are needed. We are thus interested in projecting solutions to a restricted vocabulary. Yet, the adaption of Boolean constraint solving algorithms turns out to be non-obvious provided one wants a repetition-free enumeration in polynomial space. We address this problem and propose a new algorithm computing projective solutions. Although we have implemented our approach in the context of Answer Set Programming, it is readily applicable to any solver based on modern Boolean constraint technology.

Unsatisfiability-based optimization in clasp

Answer Set Programming (ASP) features effective optimization capacities based on branch-and-bound algorithms. Unlike this, in the area of Satisfiability Testing (SAT) the finding of minimum unsatisfiable cores was put forward as an alternative approach to solving Maximum Satisfiability (MaxSAT) problems. We explore this alternative approach to optimization in the context of ASP. To this end, we extended the ASP solver clasp with optimization components based upon the computation of minimal unsatisfiable cores. The resulting system, unclasp, is based on an extension of the well-known algorithms msu1 and msu3 and tailored to the characteristics of ASP. We evaluate our system on multi-criteria optimization problems stemming from realistic Linux package configuration problems. In fact, the ASP-based Linux configuration system aspuncud relies on unclasp and won four out of seven tracks at the 2011 MISC competition.

Progress in clasp Series 3

We describe the novel functionalities comprised in clasp’s series 3. This includes parallel solving of disjunctive logic programs, parallel optimization with orthogonal strategies, declarative support for specifying domain heuristics, a portfolio of prefabricated expert configurations, and an application programming interface for library integration. This is complemented by experiments evaluating clasp 3’s optimization capacities as well as the impact of domain heuristics.