Looking for clues: solving complex problems with biologically inspired heuristics

Stewart, Paul and Chen, Jun and Fernig, David (2011) Looking for clues: solving complex problems with biologically inspired heuristics. In: Symposium AA: Frontiers in Optical Bio-imaging and Microscopy.The 6th Biennial International Conference on Materials for Advanced Technologies (ICMAT 2011), 29 June - 1 July 2011, Suntec, Singapore.

Full text not available from this repository.

Full text URL: http://www.meetmatt-conf.net/icmat2011pub/absSearc...

Abstract

Scientists and Engineers constantly face the challenge of trying to find solutions to problems which are not well understood, complex, swamped in noisy data or a combination of negative factors. Research by its very nature involves working with systems for which we don't yet have an accurate (or any!) model, systems which are generally multivariable, high order, and nonlinear. If we now throw noisy data measurements into the mix, then even relatively simple problems become intractable by 'classical methods'.
In this seminar, Professor Stewart examines problem solving methodologies, with particular emphasis on Biologically Inspired Heuristics and Meta-Heuristics, with particular emphasis on data analysis and modeling with real-world applications.

Item Type:Conference or Workshop Item (Keynote)
Additional Information:Scientists and Engineers constantly face the challenge of trying to find solutions to problems which are not well understood, complex, swamped in noisy data or a combination of negative factors. Research by its very nature involves working with systems for which we don't yet have an accurate (or any!) model, systems which are generally multivariable, high order, and nonlinear. If we now throw noisy data measurements into the mix, then even relatively simple problems become intractable by 'classical methods'. In this seminar, Professor Stewart examines problem solving methodologies, with particular emphasis on Biologically Inspired Heuristics and Meta-Heuristics, with particular emphasis on data analysis and modeling with real-world applications.
Keywords:heuristics, meta-heuristics, hyper-heuristics, biologically inspired problem solving
Subjects:G Mathematical and Computer Sciences > G700 Artificial Intelligence
Divisions:College of Science > School of Engineering
ID Code:3816
Deposited By:INVALID USER
Deposited On:09 Jan 2011 17:35
Last Modified:17 Jul 2014 10:58

Repository Staff Only: item control page