Title:	The Rules of Modelling Automatic Generation of Constraint Programs
Date:	September 13, 2005 (Tuesday)
Time:	4:30 p.m. - 5:30 p.m.
Venue:	Room 121, 1/F, Ho Sin-hang Engineering Building, The Chinese University of Hong Kong, Shatin, N.T.
Speaker:	Prof. Alan M. Frisch Artificial Intelligence Group Department of Computer Science University of York United Kingdom

ABSTRACT:

Many and diverse search problems have been solved with great success using constraint programming. However, to employ constraint programming technology to solve a problem, the problem first must be characterised, or modelled, by a set of constraints that its solutions must satisfy. Generating a correct model can be difficult; generating one that is easier to solve than its alternatives is even more difficult, often requiring considerable expertise. This so-called "modelling bottleneck" has inhibited the wider use of constraint programming technology.

This talk describes CONJURE, a rule-based system that automatically generates constraint programs by refining an abstract problem specification. Since the high-level specification language is significantly closer than a constraint program to the way in which problems are commonly conceived, the modelling bottleneck is substantially reduced. A particular focus of this talk is showing why the refinement rules must be recursive, why this is difficult to achieve and how we ultimately solved this problem.

This talk assumes no background in constraint programming.

BIOGRAPHY:

Dr Alan M Frisch is a Reader in Intelligent Systems and Head of the Artificial Intelligence Group in the Dept. of Computer Science at the Univ. of York. He previously held faculty positions at the Univ. of Illinois at Urbana-Champaign and at the Univ. of Sussex and has held visiting research positions at Max Planck Institute for Informatics, Univ. of Leeds, IBM T J Watson Research Center, AT&T Bell Laboratories and Hokkaido Univ. For almost 25 years he has been publishing research on a wide range of topics in the area of constraint programming, Boolean satisfiability, automated reasoning (including the integration of constraint solvers in deductive systems), logic programming, probabilistic inference, knowledge retrieval, and inductive generalisation. His current work focuses on developing a systematic and automatic account of the process of modelling problems with constraints.

Enquiries: Miss Temmy So at tel 2609 8444

For more information, please refer to http://www.cse.cuhk.edu.hk/seminar