Description:
This course provides a general introduction to Artificial Intelligence (AI).
Artificial intelligence covers a wide range of topics. This course
will consider philosophical, mathematical, and experimental/implementation
aspects of such topics as problem solving, searching, game playing,
genetic algorithms, logic, expert systems, reasoning under uncertainty,
fuzzy sets, learning, and neural networks.
In addition to theoretical introduction,
students will get exposure to some of the popular AI tools.
Due to time constraints, it will not be possible to study each of the
topics in great detail.
Students are expected to conduct an indepth
study of any one of the AI topics.
Brief Class Outline:
1. Introduction to Aritificial Intelligence.
2. Intelligent Agents.
3. Problem solving, seraching, genetic algorithms.
4. First order logic, expert systems.
5. Probabilistic and fuzzy systems.
6. Learning from observations, neural networks.
7. Intelligent communication, natural language processing, speech recognition.
Text:
Russell, S.J. and Norvig, P. 1995.
Artificial Intelligence: A Modern Approach,
Prentice Hall, Toronto.