Abstract
Answer Set Programming (ASP; [1,2,3]) is a declarative problem solving approach, combining a rich yet simple modeling language with high-performance Boolean constraint solving capacities. ASP is particularly suited for modeling problems in the area of Knowledge Representation and Reasoning involving incomplete, inconsistent, and changing information. As such, it offers, in addition to satisfiability testing, various reasoning modes, including different forms of model enumeration, intersection or unioning, as well as multi-criteria and -objective optimization. From a formal perspective, ASP allows for solving all search problems in NP (and NP NP) in a uniform way. Hence, ASP is wellsuited for solving hard combinatorial search problems, like system design and timetabling. Prestigious applications of ASP include composition of Renaissance music [4], decision support systems for NASA shuttle controllers [5], reasoning tools in systems biology [6,7,8] and robotics [9,10], industrial team-building [11], and many more. The versatility of ASP is nicely reflected by the ASP solver clasp [12], winning first places at various solver competitions, such as ASP,MISC, PB, and SAT competitions. The solver clasp is at the heart of the open source platform Potassco hosted at potassco.sourceforge.net . Potassco stands for the “Potsdam Answer Set Solving Collection” [13] and has seen more than 30000 downloads world-wide since its inception at the end of 2008.
The talk will start with an introduction to ASP, its modeling language and solving methodology, and portray some distinguished ASP systems.
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Schaub, T. (2013). Answer Set Programming: Boolean Constraint Solving for Knowledge Representation and Reasoning. In: Schulte, C. (eds) Principles and Practice of Constraint Programming. CP 2013. Lecture Notes in Computer Science, vol 8124. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40627-0_2
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