Faculty of Engineering and Natural Sciences
Knowledge Representation and Automated Reasoning
Wednesday, 21 May 2008, 13:40–15:30, FENS G035, 15:40–17:00,
Knowledge Representation and Automated Reasoning (KR&AR) is a vibrant and exciting field of Artificial Intelligence (AI), that has led to significant advances in practical applications in a wide range of areas in computer sciences and other sciences, such as natural language understanding, machine learning, intelligent user interfaces, robotics, multi-agent systems, semantic web, web servcies, game playing, software engineering, distributed computing, security, databases, computational biology, historical linguistics, operations research, game theory, economics. KR&AR is the study of representing knowledge explicitly in such a way that a computer can reason about it (infer appropriate knowledge from it) to behave intelligently. Explicit representations of knowledge manipulated by reasoning engines are an integral and crucial component of intelligent systems.
The AI Day at
University includes talks about recent progress on the theoretical principles underlying the representation and computational management of knowledge, and applications of KR&AR to some challenging problems in computational biology and biomedical informatics.
Vladimir Lifschitz is Gottesman Family Centennial Professor in Computer Sciences at the
Austin. His research interests are in the areas of knowledge representation and computational logic. He is a Fellow of the Association for the Advancement of Artificial Intelligence, a co-editor of the Handbook of Knowledge Representation, the Editor-in-Chief of the ACM Transactions on Computational Logic, and an Editorial Advisor of the journal Theory and Practice of Logic Programming. He has received the Publisher’s Prize at International Joint Conference on Artificial Intelligence twice, and the Most Influential Paper in 20 Years Award from the Association for Logic Programming.
AI Day Program
14:00 – 15:00 Vladimir Lifschitz,
Austin, “A New Perspective on the Semantics of Answer Set Programming”
15:00 – 15:30 Orkunt Sabuncu,
University, “Computing Answer Sets using Model Generation Theorem Provers”
15:40 – 16:00 Esra Erdem,
University, “An Overview of KR&AR Research at
16:00 – 16:30 Ferhan Türe,
University, “Efficient Haplotype Inference with Answer Set Programming”
16:30 – 17:00 Esra Erdem, Sabancı University, “A New Approach to Integrating Biomedical Ontologies and Answering Complex Queries related to Drug Discovery”