The aim of this module is to provide a general introduction to artificial intelligence, its techniques, and main subfields, suitable for students in their first term of all our core Computer Science programmes, as well as students beginning our AI half degree. There will be a main lecture and exercise class each week covering the main ideas, plus a parallel series of guest lectures covering a selection of more advanced and specialist applications.
The following table shows the module structure and lecture timetable. All the module handouts will be made available here as pdf files shortly after the paper versions have been distributed in the lectures. Spare paper copies will be deposited in the School library.
| Week |
Session 1 Tuesdays 16:00-17:00 |
Session 2 Tuesdays 17:00-18:00 |
Session 3 Wednesdays 11:00-12:00 |
|---|---|---|---|
| 1 | Module Organisation [pdf] | - |
- |
| 2 | The Roots, Goals and Sub-fields of AI [pdf] | Exercise Session 1 [pdf] | Evolutionary Computation [html] (Thorsten Schnier) |
| 3 | Biological Intelligence and Neural Networks [pdf] | Exercise Session 2 [pdf] | Neural Network Applications [pdf] (Peter Tino) |
| 4 | Building Intelligent Agents [pdf] | Exercise Session 3 [pdf] | Interacting Agent Based Systems [pdf] (Dean Petters) |
| 5 | Knowledge Representation [pdf] | Exercise Session 4 [pdf] | AI and Philosophy [html] (Aaron Sloman) |
| 6 | Semantic Networks and Frames[pdf] | Exercise Session 5 [pdf] | Natural Language Processing (Mark Lee) |
| 7 | Production Systems [pdf] | Exercise Session 6 [pdf] | Intelligent Robotics (Jeremy Wyatt) |
| 8 | Search [pdf] | Exercise Session 7 [pdf] | Computer Vision (Ela Claridge) |
| 9 | Expert Systems [pdf] | Exercise Session 8 [pdf] | Computer Chess [pdf] (Colin Frayn) |
| 10 | Treatment of Uncertainty [pdf] | Exercise Session 9 [pdf] | AI in Computer Games [pdf] (Nick Hawes) |
| 11 | Machine Learning [pdf] | Exercise Session 10 [pdf] | Machine Learning Applications (Ata Kaban) |
| 12 | Revision Lecture Covering the Whole Module [pdf] |
For students who manage to fail the examination at first attempt, there will be a resit examination in August. This will have the same format as the original examination.
For those of you interested in looking at some existing AI applications, the following links may be a good place to start:
The Recommended Books for this module are:
| Title | Author(s) | Publisher, Date | Comments |
|---|---|---|---|
| Artificial Intelligence: A Modern Approach | S. Russell & P. Norvig | Prentice Hall, 2003 | This is the book that ties in most closely with the module |
| Artificial Intelligence (2nd edn) | E. Rich & K. Knight | McGraw Hill, 1991 | Quite old now, but still a good second book |
| Artificial Intelligence: A New Synthesis | Nils Nilsson | Morgan Kaufmann, 1998 | A good modern book |
| Introduction to Expert Systems (3rd edn) | Peter Jackson | Addison Wesley, 1999 | The best book on Expert Systems |
| Artificial Intelligence (3rd edn) | Patrick Winston | Addison Wesley, 1992 | A classic, but not advanced enough now |
| Artificial Intelligence | Rob Callan | Palgrave Macmillan, 2003 | A good modern book |
| Artificial Intelligence | Michael Negnevitsky | Addison Wesley, 2002 | A good modern approach |
| Artificial Intelligence (5th edn) | George Luger | Addison Wesley, 2004 | Some students may prefer this one |
If you can only afford to buy one book for this module, I would recommend getting the one by Russell & Norvig.