Next: Security
Up: Lent Term 1999: Part
Previous: Neural Computing
Lecturer: Dr W.F. Clocksin
(wfc@cl.cam.ac.uk)
No. of lectures: 12
Prerequisite course: Prolog for Artificial Intelligence
- Problems and challenges.
- Why is something that looks so easy to do actually so difficult to
compute?
- Theories and methods.
- What approaches have been tried?
- AI programming.
- What is LISP for, and how does it relate to Prolog?
- Constraints.
- How can one exploit the natural structure of a problem in order to
solve it?
- Knowledge representation.
- What are the problems with representing commonsense knowledge?
- Reasoning.
- What formal methods are there for dealing with ill-posed problems?
- Inference.
- What follows from what? How do you know it does?
- Fuzzy logic.
- How can one compute and control using approximations in the absence of
a model of the process?
- Qualitative control.
- How little precision can you get away with?
- Search.
- What are some ways of looking for something?
- Planning.
- How can you figure out what to do before you do it?
- Decision making.
- What is a basis for making a decision, and why does it matter?
Recommended books:
Russell, S. & Norvig, P. (1995). Artificial Intelligence: A
Modern Approach. Prentice-Hall.
Shoham, Y. (1994). Artificial Intelligence Techniques in
Prolog. Morgan Kaufmann.
Next: Security
Up: Lent Term 1999: Part
Previous: Neural Computing
Christine Northeast
1998-10-01