Module 11352 (2003)
Syllabus page 2003/2004
06-11352
AI Techniques A
Level 1/C
Links | Outline | Aims | Outcomes | Prerequisites | Teaching | Assessment | Books | Detailed Syllabus
The Module Description is a strict subset of this Syllabus Page. (The University module description has not yet been checked against the School's.)
Relevant Links
See AI Techniques A
Web-page for module material and further useful links.
Outline
This module provides a general introduction to artificial intelligence and its techniques. An overview on the main subfields of artificial intelligence will be given. The main focus of the module will be on the common underlying ideas, such as knowledge representation, search, rule based systems, and learning.
Aims
The aims of this module are to:
- provide a general introduction to artificial intelligence and its techniques
- give an overview of the key ideas such as knowledge representation, search, rule based systems, and learning that underly the main subfields of artificial intelligence
- demonstrate the need for different approaches for different problems
Learning Outcomes
| On successful completion of this module, the student should be able to: | Assessed by: | |
| 1 | structure the field of artificial intelligence into its main subfields, and outline the important features of AI systems | Continuous assessment, examination |
| 2 | explain some of the most important knowledge representation formalisms and understand why there are different ones, discuss their advantages and drawbacks, and represent knowledge in unseen easy examples in any of them | Continuous assessment, examination |
| 3 | apply simple un-informed search algorithms | Continuous assessment, examination |
| 4 | understand the processes involved in Expert Systems and in building such systems | Continuous assessment, examination |
| 5 | discuss the importance of learning for intelligent systems | Continuous assessment, examination |
| 6 | provide examples of different types of AI systems, and explain their differences, common techniques, and limitations | Continuous assessment, examination |
Restrictions, Prerequisites and Corequisites
Restrictions:
None
Prerequisites:
None
Co-requisites:
06-11353 (AI Techniques B) (linked module)
Teaching
Teaching Methods:
3 hrs/week of lectures and exercise classes
Contact Hours:
Assessment
- Supplementary (where allowed): As the sessional assessment
- 3 hr examination (80%), continuous assessment (20%), divided equally between this module and 06-11353 (AI Techniques B). Resit by examination only.
Recommended Books
| Title | Author(s) | Publisher, Date |
| Artificial Intelligence: A Modern Approach (2nd edn) | S Russell & P Norvig | Prentice Hall, 2003 |
| Artificial Intelligence (2nd edn) | E Rich & K Knight | McGraw Hill, 1991 |
| Artificial Intelligence: A New Synthesis | N J Nilsson | Morgan Kaufmann, 1998 |
| Artificial Intelligence | Rob Callan | Palgrave Macmillan, 2003 |
| Artificial Intelligence (4th edn) | G Luger | Addison Wesley, 2002 |
| Artificial Intelligence | M Negnevitsky | Addison Wesley, 2002 |
| Artificial Intelligence (3rd edn) | P H Winston | Addison Wesley, 1992 |
| Expert Systems (3rd edn) | P Jackson | Addison Wesley, 1999 |
Detailed Syllabus
- Introduction to the AI Programme
- The roots, goals and subfields of AI
- Evolutionary Computation
- Biological Intelligence and Neural Networks
- Brain Modelling
- Building Intelligent Agents
- Behaviourism and Cognitivism
- Knowledge Representation
- Cognitivism and Robots
- Semantic Networks
- Frame Based Systems
- Production Systems
- Vision
- Uninformed Search
- Natural Language Processing
- Expert Systems
- Treatment of Uncertainty
- Machine Learning
- Computer Chess
- Limitations and Misconceptions of AI
- Philosophical Issues
Last updated: 1 Feb 2004
Source file: /internal/modules/COMSCI/2003/xml/11352.xml
Links | Outline | Aims | Outcomes | Prerequisites | Teaching | Assessment | Books | Detailed Syllabus