Module 18184 (2004)
Syllabus page 2004/2005
06-18184
AI & Cognitive Science
Level 1/C
Unknown/Left:15
John Barnden:10
William Edmondson (coordinator)
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.)
Changes and updates
New module for 2004/05 (in part replaces AI Techniques B and Logic).
Relevant Links
See the Module Web Page for module information and resources.
Outline
This module provides a general introduction to Artificial Intelligence and Cognitive Science, including an introduction to each of their main subfields. The focus of the module is on AI as a science of intelligence.
Aims
The aims of this module are to:
- provide a general introduction to the techniques and theories of Artificial Intelligence and Cognitive Science, building on material provided elsewhere
- present Artificial Intelligence as a computational theory of intelligence
- give a deeper understanding of themes such as representation, heuristics and search that underly the main subfields of AI
- introduce logic as a formalism for representation and reasoning
- 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 | describe the ideas, issues, problems and techniques in some of the main subfields of Artificial Intelligence and Cognitive Science, including Cognitive Psychology, Search, Rule Based Systems, Logic, Reasoning, Vision, Robotics, Natural Language Processing and Adaptive Computation | Continuous assessment, examination |
| 2 | identify and describe some basic structures and mechanisms forming the biological basis of intelligent behaviour | Continuous assessment, examination |
| 3 | explain and discuss some computational models in Cognitive Science | Continuous assessment, examination |
| 4 | discuss the philosophical issues arising from such computational models | Continuous assessment, examination |
| 5 | explain the most important knowledge representation formalisms and why they are needed, discussing their advantages and disadvantages | Continuous assessment, examination |
| 6 | apply these knowledge representation formalisms to example problems | Continuous assessment, examination |
| 7 | employ the first order predicate calculus as a formalism for representation and reasoning | Continuous assessment, examination |
| 8 | describe the uses and limitations of logic in AI and discuss alternatives | Continuous assessment, examination |
| 9 | describe, analyse and critically discuss a variety of AI techniques and apply them to example problems | Continuous assessment, examination |
| 10 | provide examples of AI systems and applications, and explain common techniques, differences and limitations | Continuous assessment, examination |
| 11 | explain and apply simple experimental techniques to AI and Cognitive Science problems | Continuous assessment, examination |
Restrictions, Prerequisites and Corequisites
Restrictions:
None
Prerequisites:
None
Co-requisites:
06-18188 (Introduction to AI), 06-18185 (AI Programming)
Teaching
Teaching Methods:
3 hrs/week of lectures and exercise classes in Semester 1, 4 hrs/week in Semester 2
Contact Hours:
Assessment
- Supplementary (where allowed): As the sessional assessment
- 2 hr examination (60%), continuous assessment (40%). 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: A New Synthesis | N J Nilsson | Morgan Kaufmann, 1998 |
| Artificial Intelligence | Rob Callan | Palgrave Macmillan, 2003 |
Detailed Syllabus
- Cognitive Psychology
- Cognitive Science
- Informed Search and Planning
- Rule Based Systems
- Propositional Logic
- Predicate Logic
- Resolution theorem proving
- Vision and Robotics
- Natural Language Processing
- Experimental techniques
- Reasoning
- Knowledge Representation
- Limitations and Misconceptions of AI
- Philosophical Issues
Last updated: 5 Nov 2004
Source file: /internal/modules/COMSCI/2004/xml/18184.xml
Links | Outline | Aims | Outcomes | Prerequisites | Teaching | Assessment | Books | Detailed Syllabus