| Delivery Type | Delivery length / details |
|---|---|
| Lecture | 20 Hours. |
| Practical |
| Assessment Type | Assessment length / details | Proportion |
|---|---|---|
| Semester Exam | 2 Hours | 100% |
| Supplementary Exam | Will take the same form, under the terms of the Department's policy. |
On successful completion of this module students should be able to:
describe the importance of propositional and predicate logic in Artificial Intelligence systems;
;
* solve simple problems in propositional and first order predicate logic
write Prolog programs to solve simple AI problems
* explain the function and use of fuzzy logic
*explain the application of Bayesian probabilty to simple reasoning scenarios;
Artificial Intelligence (AI) has made many important contributions to computer science in general, and most experts believe AI techniques will become increasingly important. This module follows on from the introduction to the fundamental concepts of AI given in CS26110 . Key issues including knowledge representation, reasoning and the problem of approximate information are addressed both theoretically and practically.
Artificial Intelligence is the study of computer systems which can perform the sort of tasks that are usually associated with human intelligence. Examples are: chess playing, pattern recognition, speech understanding and problem solving. The aim of this module is to introduce the main ideas and current problems in Artificial Intelligence including the key concepts of knowledge representation, reasoning and the problem of approximate information. Students will be required to implement and utilise these concepts by means of an Artificial Intelligence programming language.
This module is at CQFW Level 5