CS540 Spring 2008 Project

We will discuss semester projects at the beginning of class. They may consist of an application using a publicly available AI system or tool, overviews of new hot topics, implementations of artificial intelligence techniques other than those developed in class, application of discussed techniques to real problems, replication of a prior study, or some combination of the above. The project should include some implementation or evaluation component.

Because other graduate AI courses are taught in computer vision, statistical machine learning and bioinformatics, your project must focus on an AI topic outside of those areas. You may include some aspect of the topics covered in other classes as a minor part for comparison or to provide some needed functionality, but other areas must not be the focus.

If you are in doubt, come talk to the instructor.
If you are also taking CS545 and want to pursue a larger project that satisfies requirements in both courses, come talk to the instructors.
If you want to work in a team, come talk to the instructor.

Project proposals must be submitted by February 11. Proposals should be 1-2 pages, which briefly describe what problem is being solved or question(s) answered, if it is a team or joint CS545 or CS510 project, why it is appropriate for this course. Include any citations or background information sketching what has been done before. Note: I must see at least one citation to demonstrate that you've at least checked what has been done before. Citation should be of a paper that was published in a peer reviewed venue (conference, workshop or journal); some random person's web site, blog or unrefereed student paper does not count.

At some time during the semester, you will do a progress report; size permitting, we will do them in class. During the last week of the semester, each project will be presented to the class. A written report describing what was done is also required.

Project titles from Spring 2005:

Uninformed World Exploring Agents
Alternative Data Mining Techniques for Predicting Tropical Storm Intensification
Examining Move Operators for Dynamic Basis Function
Using Genetic Algorithms to Weight an Evaluation Function for Tetris
Evolving Cellular Automata to Perform Computation
Learning trust in multi-agent systems using belief (Bayesian) networks

Project titles from Spring 2006:

Particle Swarm Intelligence and Multi-funnel functions
Comparison of GA strategies on traclabs' BIOSIM
Two Heuristics for Resource Allocation in a Heterogeneous computing System
Empirical Studies in Genetic Algorithms and Genetic Programming using the Game of Othello
Using AI To Guide Performance Transformations For Irregular Applications
Cracking Transposition Ciphers
Habitat longevity optimization using genetic algorithms
Application of Genetic Algorithms to the Dynamic Job Shop Problem
A Fuzzy Clustering approach to filter Spam E-Mail

Project titles from Spring 2008:

Literature Based Discovery
Automatic Tower Defense
Bounding Local Minima and Plateaus in Image Congealing
Elevator Dispatching Problem
A Different Approach for SLS-THC: Stochastic Local Search Algorithm with Violations-Directed Random Walk