Artificial Intelligence Principles (Semester 2 - Spring 2009): Course material and useful links

Dr Dean D. Petters

Aims and Learning Outcomes

Aims and Learning Outcomes for the Course can be found on the
Module Description Page. You should look at these when preparing your student presentations. All the presentations should together provide some of the breadth required by the learning outcomes.


This half of the module provides 50% of the credit for the whole module. There are three forms of assessment in this half of the module:

a terminal exam

an open book class test on logic (20% of the credit for this half of the module, which is 10% of the entire module)

student presentations (20% of the credit for this half of the module, which is 10% of the entire module)
(Deadline for emailing me with a planned subject for your presentation: 6th February)

Assessment criteria for the student presentations can be found

Retakes will be solely by examination.

Course structure and provisional content (things may change during the course)

The course will include lectures, problem classes, and student presentations.

The problem classes will cover problems that were set in previous weeks(hence no problem class and an extra lecture in the first week).

Sessions with a red background involve continuous assessment. There will be a class test on logic and student presentations which are assessed. Students will be assessed according to their own presentations and contributions that they make to the presentations of other students (an important contribution for each student being the attendance of other students presentations!).

Presentations are intended to provide breadth to the course from areas of AI of interest to the students. The subject of presentations can be drawn from three broad areas: history of AI; boundaries of Cognitive Science; and AI applications. Presentations should include material on AI representations and techniques, attempting a critical evaluation.

Deadline for emailing me with a planned subject for your presentation: 6th February

There will be a number of laboratory based demonstration classes, these will occur at 5-6pm on Thursdays (that is immediately after the Thursday afternoon session). The actual number of, and dates, for these classes remains to be confirmed.

Slides for the lectures and exercise sheets for the problem classes will be linked from this table as the module progresses.

Week Session 1 (Thursday 10 am, G22, Nuffield Building)Session 2 (Thursday 11 am, room G22, Nuffield Building) Session 3 (Thursday 1pm, room G22, Nuffield Building)
week 1, Thursday 15th January Lecture - History of AI and Cognitive Science, GOFAI versus nouvelle AI, AI in SoCS, route map for the course

[pdf] [ppt]
Lecture - AI, modelling and simulation. Paradigms, frameworks, theories, models, simulations. Craik - Nature of Explanation. The boundaries of Cognitive Science. Overview of possible AI applications for student presentations

[pdf] [ppt]
Lecture - Search - Romanian route finding with a faulty sat-nav

[pdf] [ppt]
week 2, Thursday 22th January Problem class - Search

[pdf] [doc]
Lecture - Logic 1 - Argument, validity and soundness of arguments, formal systems and semantics

Lecture - Logic 2 - Propositional logic, connectives, Truth Tables, formalising English, Entailment and soundness and completeness of inference systems

week 3, 29th January Problem class - Logic


Lecture - Logic 3 - Inference in Propositional Logic, FOPL, predicates, quantification, scoping, English to FOPL

Lecture - Logic 4 - Automated logical reasoning. Other types of logic, including modal, temporal, and fuzzy logic.

week 4, 5th February Problem class - Logic


Lecture - Planning

Lecture Knowledge representation -

week 5, 12th February Problem class - Planning

Problem class - Knowledge representation

Logic revision
week 6, 19th February Logic revision Lecture - Biological Intelligence,

Lecture - Interacting agent based systems [pdf]

week 7, 26th February Problem class - Biological Intelligence

Lecture - Vision

Logic Class Test

week 8, 5th March Problem class - Vision

Lecture Learning

Student presentations

week 9, 12th March Lecture - Learning [pdf] Alec - Turing Test

Talha - Visual AI

Student presentations

Sam - Searle's Chinese Room

Jordan - CogVis
week 10, 19th March Problem class -TBA Student presentations

Chris - The Theory of Consciousness In AI

David - TBA
Student presentations

Fran - Strong AI and Chatterbots

Matthew - Reactive and Hybrid Agents
11 Logic class test review - marks and answers

Revision Further Search Problems (from week 1 Problem sheet)

Recommended AI Text Books and additional references for this half of the module

Further references will be listed here, and photocopies of specific papers and book chapters put in the module box in the school library, as the module progresses.

Title Author(s) Publisher, Date Comments
Artificial Intelligence Rob Callan Palgrave Macmillan, 2003 REQUIRED FOR THE MODULE: A good modern book with up to date coverage of applications. Ties in closely with the module
Artificial Intelligence: A Modern Approach S. Russell & P. Norvig Prentice Hall, 2003 A good modern book that also ties in closely with the module. More detailed than Callan, but also more introductory material to difficult topics
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 Michael Negnevitsky Addison Wesley, 2002 A good modern approach, though doesn't cover some of the core ideas in the module. Good up to date material on applications
Artificial Intelligence (5th edn) George Luger Addison Wesley, 2004 Good up to date book, advanced material and up to date applications.
Mind as Machine: A History of Cognitive Science. Two Volume set. Margaret BodenClarendon Press, 2006 Right up to date and packed with lots of information about History of AI as well as Cognitive Science. All the major researchers are found in here.
The Mind's New Science Howard GardnerBasic books, 1985 Not up to date, but very good on the multiple disciplines that make-up Cognitive Science and a good historical review of AI in chapter six. Valuable material for student presentations
Mind: Introduction to Cognitive Science Paul ThagardBradford book, 1996 Good introduction to the Computational and Representational Understanding of Mind (CRUM). Valuable material for student presentations on subjects such as: AI and emotion and consciousness (chapter nine), embodied and situated cognition (chapter ten), AI and dynamic systems and mathematical knowledge (chapter eleven)
Mind Design II John HaugelandMIT Press, 1997 Philosophically oriented. Key papers by Turing (chapter 2); Newell and Simon (chapter 4); Minsky (chapter 5); and Searle (chapter 7); and many others; that might form part of student presentations.
Being there: Putting Brain, Body and World Together Again Andy ClarkMIT Press, 1997 Readable introduction that a makes the case for the Embodied cognition approach in AI. Useful material for a presentation
Artificial Minds Stan FranklinBradford book, 1997 A readable introduction to AI and some material for presentations
Thinking on the Web: Berners-Lee, Godel, and Turing H. Peter Alesso and Craig F. SmithWiley 2006 Presents the challenge of creating the semantic web from an AI perspective
The Society of Mind Marvin MinskySimon and Schuster, 1985 Background material: a classic, may be used for a presentation on Minsky's contribution to AI
The Sciences of the Artificial Herbert SimonMIT Press 1996 Background material: a classic, may be used for a presentation on Simon's contribution to AI
Matter and consciousness Paul ChurchlandMIT Press, 1999 Background material: readable introduction to Philosophy of Mind
Godel, Escher Bach Douglas HofstaderBasic Books, 1979 Background material: a classic that brings together work from AI, psychology, music and the visual arts in search of how a 'self' can be formed from inanimate matter. Lots of material that deals with formal systems, logic, and issues in theoretical computer science and AI with a very readable manner

Useful Links for planning your Presentations

These links have been taken from John Bullinaria's Intro to AI page from last year. They should be helpful in choosing a subject for your presentations. If you find any more relevant websites, let me know and I'll add them in:

Here are some extra links added this year

List of student presentations - to get your presentation on this list email

Student Subject of presentation
ug73bxp Machine emotions
ug85jxh Machine emotions/consciousness
ug76jxl Turing test
ug73djp Hume and Kant
ug76rgg Computers with common sense - the CYC project
ug73tas Strong AI
ug44aom AI in games
ug69pxb Minsky: Life and works
ug63txw Searle and Chinese Room