Recent Advances Defining the Semantics of Answer Set Programming based Languages.
Speaker: Yuanlin Zhang
Texas Tech University
Answer Set Programming becomes a dominant paradigm in the Knowledge Representation research community. I have been applied to solve numerous problem, and it has been continuously expanded to address new challenges. In this talk, we will discuss challenges resulted from the expansion of the languages to include aggregates and modal operators. New techniques are introduced to define/understand the semantics of aggregates and modal operators. They are based on and a natural extension of the set of simple principles employed for defining the classical semantics of Answer Set Programming.
Bio: Yuanlin Zhang is an associate professor of computer science. His research interests are in the general area of Artificial Intelligence and its applications to address challenging problems. His recent research focus is on the semantics of Answer Set Programming based languages, the architecture for intelligent systems and their applications to areas such healthcare and education.