Answer Set Programming and Automatic Optimization Methods in its Realm
Answer set programming is a popular constraint programming paradigm that has seen wide use across various industry applications. However, logic programs under answer set semantics sometimes require careful design and nontrivial expertise from a programmer to obtain satisfactory solving times. In order to reduce this burden on a software engineer we propose an automated rewriting technique for non-ground logic programs that we implement in a system PROJECTOR. We conduct rigorous experimental analysis, which shows that applying system PROJECTOR to a logic program can improve its performance, even after significant human-performed optimizations. This talk will present answer set programming, system PROJECTOR, the theory behind the system, and considered experimental analysis.
Bio: Yuliya Lierler is an associate professor at the Computer Science Department at the University of Nebraska Omaha. Prior to coming to the University of Nebraska, Dr. Lierler was a Computing Innovation Fellow Postdoc at the University of Kentucky. She holds a Ph.D. in Computer Sciences from the University of Texas at Austin. Dr. Lierler’s research interests include the field of artificial intelligence, especially in the area of knowledge representation, automated reasoning, declarative problem solving, and natural language understanding.