CPSC 532D - Stochastic Search Algorithms (Spring 2005)

[General Info] · [Course Outline] · [Course Projects] · [Grading] · [Assignments] · [Resources]
Latest news (04/12): Slide sets for Modules 11+12 are now available from the "Resources" section.

General / Administrative Information

Course number / title: CPSC 532D (203): Topics in Artificial Intelligence - Stochastic Search Algorithms

Time and Location: Tue+Thu 11:00-12:30 in DEMP 201 (New Dempster Pavilion)
First Class: Thu, 11 January 2005

Instructor: Holger Hoos

[Current official information on graduate courses in 2004/05 Term 2 can be found here]


Why Take This Course?

If you always wanted to learn about state-of-the-art approaches to combinatorial problem solving, including Simulated Annealing, Genetic Algorithms, Tabu Search, and Ant Colony Optimisation, this course is for you!

If you always wondered how hard problems from many domains, including AI, Bioinformatics, and Electronic Commerce, are solved in practice, this course will introduce you thoroughly to at least one very popular and successful general approach.

And if you want to learn (more) about one of the hottest topics in AI, Operations Research, and Empirical Algorithmics research, you've found the right place!

The course will introduce many basic stochastic search methods and their most relevant variants, point out and discuss connections and differences between them, tell you implementation tricks and details which are hardly ever explained but essential to obtain good performance, and show you how these algorithms can be applied to many hard combinatorial problems from various domains, including AI, Operations Research, and Bioinformatics! The course will introduce you to the foundations of stochastic search and many of its very successful applications. It will provide you with a good balance of abstract and theoretical contents as well as with hands-on-experience (including implementation).

To date, designing stochastic search algorithms and applying them successfully to hard combinatorial problems is as much an art or a craft as it is a science. I will introduce you to both aspects of this exciting research area, and share many of my secrets with you ;-) The course will be mostly based on my new book "Stochastic Local Search: Foundations and Applications" (available for browsing at the ICICS/CS Reading Room and the UBC bookstore), but in many ways we will go beyond what you can easily find in this book or anywhere else in the research literature.

Interested? Check out the in information in the following sections ...

Course Description & Prequisites

Preliminary Course Outline


Assignments


Resources

Slides (as used in class):


last update 05/04/12, hh