CPE/CSC 480-F06 Artificial Intelligence Fall 2006 Project Topics

Collaboration with Others

• Prof. David Gillette from the English department has an ongoing project, Lumiere Ghosting . The goal of this project is to allow people to immerse themselves into a virtual environment via avatars created from their picture. He is interested in collaboration with CSc students, e.g. to endow the avatars with some rudimentary intelligence, or to add computer-based agents into the environment.
• Dr. John Dalbey is working on a variation of Solitaire
• Dr. Kevin O'Gorman (the game of Hex)
• Dr. Doug Cerf from the Business School has an ongoing project, Charity Window, that provides information about charities. He is interested in adding an information gathering capability to the system that searches the Web for information about charities in their system.

Further Project Ideas

• Games: Computer games are concentrating more and more on AI techniques e.g. to generate more credible agents. Of course many of you know much more about such games than I do ;-)
• Artificial Life: The simulation of "creatures" (e.g. walkers, crawlers, worms) or populations (swarms of birds, ant hills, bee hives) frequently based on evolutionary or genetic algorithms.
• Genetic Algorithms: Conceptually a variation of search algorithms, these techniques are useful for certain optimization tasks, based on the "survival of the fittest" principle People have applied it to VLSI layout, scheduling, code generation, design optimization, and other, more exotic tasks.
• Neural Networks: These collections of simple computational elements are one of the frequently used learning methods in AI. They are used for tasks requiring classification or categorization, generalization from examples, or identification of similarities.
• Fuzzy Logic: In contrast to standard logic with its binary values, fuzzy logic employs linguistic variables such as "very tall" to capture the essential aspects. This makes many tasks such as process control much easier, but requires different reasoning methods.
• Robotics: The use of physical agents often illustrates the difference between easily solvable toy problems and their counterparts in the real world. I have one simple "Lego robot" that can be programmed in Java or a C-like language.
• Natural Language Processing: With building blocks such as Link Grammar or WordNet, it is possible to construct systems that extract meaningful information from text-based documents.
• Semantic Web: The Semantic Web adds additional information to Web pages in the form of meta-tags. This enables computers to perform more meaningful operations on Web pages. For example, it allows the search for concepts based on ontologies, rather than simple keywords.