报告简介:
Logic based problem solving approaches, such as propositional satisfiability problem, relational calculus, Satisfiability Modulo Theories, prolog, Datalog, circumscription and default logic, is one of the central topics in computer science, and has profound applications to many related areas, e.g., software engineering, artificial intelligence, database, WWW, information security, bioinformatics and so on. More importantly, in the last decade, significant progresses have been made to implement these logical formalisms for solving real world problems.
This talk is about Answer Set Programming, a traditional yet modern logic based declarative programming paradigm, which has its root deeply planted in the above logic approaches but with new and promising features. We reconstruct the foundation of Answer Set Programming, and show that it is deeply related to all the above logic approaches. Based on these theoretical results, we present a new direction of answer set solving, whose promising future is evidenced by a first implementation. We also discuss some deep relationships between Answer Set Programming and computational complexity, e.g. the P vs NP problem.
报告人简介:
Dr. Yi Zhou is now a lecturer at the Artificial Intelligence Research Group in University of Western Sydney. His research focuses on logic foundations in computer science and artificial intelligence, and their applications to other areas in computer science, e.g., model checking and verification, AI planning, information security, WWW and so on. His recent publications include 4 articles in the predominant AI journal � Artificial Intelligence. More details can be found in his website: https://staff.scm.uws.edu.au/~yzhou/