Module 20417.1 (2007)

Syllabus page 2007/2008

06-20417
AI Principles

Level 1/C

John Barnden
Dean Petters
John Barnden (coordinator)
10+10 credits in Semester 1 and Semester 2

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

For module material and further useful links, see:
Semester 1 Web Page
Semester 2 Web Page


Outline

The module provides a general introduction to Artificial Intelligence and Cognitive Science, including an introduction to each of their main subfields. It presents AI as a science of intelligence.


Aims

The aims of this module are to:

  • provide a general introduction to Artificial Intelligence (AI), its techniques and its main subfields, emphasizing the computational aspects
  • show the relationships between Cognitive Science and AI
  • give an overview of some key underlying ideas
  • demonstrate the need for different approaches for different problems
  • provide a foundation for further study of specific areas of AI

Learning Outcomes

On successful completion of this module, the student should be able to: Assessed by:
1recognise the important features of AI systems Examination
2describe and apply some simple search algorithms Examination
3outline the processes involved in rule-based systems and in building such systems Examination
4discuss the importance of learning in intelligent systems, and how it can be implemented Examination
5provide examples of AI systems and applications, and explain common techniques, differences and limitations Continuous Assessment, Examination
6provide examples of different types of AI systems, and explain their differences, common techniques, and limitations Continuous Assessment, Examination
7describe and evaluate some of the most important knowledge representation formalisms and explain why they are needed, discussing their advantages and disadvantages Continuous Assessment, Examination
8apply these knowledge representation formalisms to unseen examples Continuous Assessment, Examination
9describe and discuss Cognitive Science, its subfields and relationship to AI, and some computational models in Cognitive Science Examination
10employ the first order predicate calculus as a formalism for representation and reasoning, and describe its strengths and limitations Continuous Assessment, Examination

Restrictions, Prerequisites and Corequisites

Restrictions:

None

Prerequisites:

None

Co-requisites:

06-18185 (AI Programming)


Teaching

Teaching Methods:

3 hrs/week of lectures, guest seminars, and exercise sessions

Contact Hours:

72


Assessment

  • Sessional: 3 hr examination (80%), continuous assessment (20%).
  • Supplementary (where allowed): Resit by examination only.

Recommended Books

TitleAuthor(s)Publisher, Date
Artificial IntelligenceRob CallanPalgrave Macmillan, 2003
Artificial Intelligence: A Modern ApproachS. Russell & P. NorvigPrentice Hall, 2003
Artificial Intelligence (2nd edn)E. Rich & K. KnightMcGraw Hill, 1991
Artificial Intelligence: A New SynthesisNils NilssonMorgan Kaufmann, 1998
Introduction to Expert Systems (3rd edn)Peter JacksonAddison Wesley, 1999
Artificial Intelligence (3rd edn)Patrick WinstonAddison Wesley, 1992
Artificial IntelligenceMichael NegnevitskyAddison Wesley, 2002
Artificial Intelligence (5th edn)George LugerAddison Wesley, 2004
Mind as Machine: A History of Cognitive Science. Two Volume set.Margaret BodenClarendon Press, 2006
The Mind's New ScienceHoward GardnerBasic Books, 1985
Mind: Introduction to Cognitive SciencePaul ThagardBradford, 1996
Mind Design IIJohn HaugelandMIT Press, 1997
Being there: Putting Brain, Body and World Together AgainAndy ClarkMIT Press, 1997
Artificial MindsStan FranklinBradford, 1997
Thinking on the Web: Berners-Lee, Godel, and TuringH. Peter Alesso and Craig F. SmithWiley, 2006
The Society of MindMarvin MinskySimon and Schuster, 1985
The Sciences of the ArtificialHerbert SimonMIT Press, 1996
Matter and consciousnessPaul ChurchlandMIT Press, 1999
Godel, Escher BachDouglas HofstaderBasic Books, 1979

Detailed Syllabus

  1. History of AI and Cognitive Science
  2. AI, modelling and simulation
  3. Search
  4. Logic
    • Introduction
    • Propositional logic
    • First order predicate calculus
    • Automating logical reasoning
    • Introduction to other forms of logic
  5. Levels of description in cognitive science
  6. Rulebase arithmetic
  7. Learning
  8. Knowledge Representation
    • Semantic networks
    • Frames
    • Semantic Web
  9. Planning
  10. Uncertainty
  11. Putting it all together

Last updated: 9 Oct 2007

Source file: /internal/modules/COMSCI/2007/xml/20417.xml

Links | Outline | Aims | Outcomes | Prerequisites | Teaching | Assessment | Books | Detailed Syllabus