CPE/CSC 480 F03 Artificial Intelligence Fall 2003
Project Topics
This document provides more details on possible topics for team projects.
Collaboration with Others
I'm in contact with other people who are currently involved in projects
related to our course topics.
We will have presentations by some of my colleagues on the following topics:
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.
The topics from the Spring 2003 CSC 580 class on Knowledge Management
might also be of interest: CSC 580 Spring 2003
Further Project Ideas
And here are a few more ideas for project topics:
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.