Herr Prof. Schaub
Knowledge Representation and Reasoning via Answer Set Programming
11.00 Uhr, 1/336
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Inhalt:The field of Knowledge Representation and Reasoning is central to Artificial Intelligence. Interestingly, the field has been going through a methodological shift during recent years. While the past was dominated by query-oriented reasoning, model-based techniques become more and more popular nowadays. This is accompanied by the availability of highly efficient general purpose problem solvers, among which Satisfiabilty and Answer Set solvers are the most prominent ones. The general idea is then to translate an application problem into a logical specification. This specification is in turn passed to a solver, which outputs models representing solutions to the initial application problem. The talk will provide an introduction to Answer Set Programming (ASP), in which applications are specified in terms of sets of logical rules. ASP has its roots in deductive databases, nonmonotonic reasoning and declarative programming. It is closely related to constraint satisfaction and propositional satisfiability. And it has already been proved to be an effective tool in a range of applications from planning to model checking to combinatorics and combinatorial optimization.