Semester 2 G64FAI Foundations of Artificial Intelligence

This module aims to give students a firm grounding in the fundamental theories and techniques of Artificial Intelligence.

Topics covered include problem solving and search, knowledge representation and reasoning, and machine learning.

Outline Syllabus

The module focuses on five main themes:

1. Introduction to Artificial Intelligence
2. Problem solving and search
3. Knowledge representation and reasoning
4. Machine learning
5. Agent-based systems

Lectures

Lectures are on Tuesdays at 1pm in room A24 in the Business School South Building (underneath the main auditorium), and on Fridays at 9am in room A25, also in Business School South Building.

Recommended Reading

The recommended text book for the module is:

• Russell & Norvig (2003), Artificial Intelligence: A Modern Approach, Prentice Hall,

or the 1995 first edition, which covers all the material needed for the module. The syllabus of G64FAI is similar to the Russell & Norvig one quarter course, with emphasis on reasoning and expert systems. Note: the newly released third edition is also acceptable, although the chapter numbers may vary.

Further Reading

Alternatives to the Russell & Norvig book include:

• Negnevitsky (2002), Artificial intelligence : a guide to intelligent systems, Addison-Wesley.
• Cawsey (1998), The essence of artificial intelligence, Prentice Hall.
• Luger (2005), Artificial intelligence : structures and strategies for complex problem solving. 5/6th Edition, Addison-Wesley.
• Nilsson (1998), Artificial Intelligence: a new synthesis, Morgan Kaufmann.

Note that there is also a version of the reading list with links to the University Library catalogue.

Other Resources

The AAAI library has topic pages on many of topics covered in the module which you may find useful for background.

Suggested Reading

Note that the following list of suggested reading is provisional, as it may necessary to change the order in which topics are presented.

• Lecture 1: Module Overview.
• Lecture 2: Introduction to AI. Russell & Norvig (2003) chapters 1 and 26.
• Lecture 3: Problem Solving & Search I. Russell & Norvig (2003) chapter 3.
• Lecture 4: Problem Solving & Search II. Russell & Norvig (2003) chapter 4.
• Lecture 5: Local Search Methods. Russell & Norvig (2003) chapter 4, section 4.4.
• Lecture 6: Propositional Calculus. Russell & Norvig (2003) chapter 7, sections 7.3, 7.4 and 7.5.
• Lecture 7: Propositional Calculus II. Russell & Norvig (2003) chapter 7, sections 7.5 and 7.6.
• Lecture 8: Predicate Calculus I. Russell & Norvig (2003) chapter 8.
• Lecture 9: Expert Systems. Russell & Norvig (2003) chapter 8, section 8.4; chapter 9, section 9.3.
• Lecture 10: Reasoning about Actions I. Russell & Norvig (2003) chapter 11, sections 11.1, 11.2, 11.3 and 11.5.
• Lecture 11: Reasoning about Actions II. Russell & Norvig (2003) chapter 11, sections 11.1, 11.2, 11.3 and 11.5.
• Lecture 12: Default reasoning. Russell & Norvig (2003) chapter 10, sections 10.7 and 10.8.
• Lecture 13: Representing and reasoning with uncertainty I. Russell & Norvig (2003) chapter 14, sections 14.1, 14.2, 14.3, 14.4 and 14.7.
• Lecture 14: Representing and reasoning with uncertainty II. Russell & Norvig (2003) chapter 14, sections 14.1, 14.2, 14.3, 14.4 and 14.7.
• Lecture 15: Learning. Russell & Norvig (2003) chapter 18, sections 18.1, 18.2 and 18.3.
• Lecture 16: Decision trees. Russell & Norvig (2003) chapter 18, 18.2 and 18.3.
• Lecture 17: Neural networks. Russell & Norvig (2003) chapter 20, 20.5 and 20.7.
• Lecture 18: Software agents I. Russell & Norvig (2003) chapter 2.
• Lecture 19: Software agents II.
• Lecture 20: Revision.

Lecture Slides

Warning: the slides are not `lecture notes': they are there to help present the material, not to act as a reference to the main points covered in the lecture. Simply reading the slides won't necessarily give you a good grasp of the syllabus. They are specifically not a substitute for taking your own notes or reading the suggested reading for the lecture.

Slides will appear here shortly before each lecture.

• Lecture 1: Module Overview Slides Slides (2 per page)
• Lecture 2: Introduction Slides Slides (2 per page)
• Lecture 3: Problem solving and search I Slides Slides (2 per page)
• Lecture 4: Problem solving and search II Slides Slides (2 per page) (Updated!)
• Lecture 5: Local search Slides Slides (2 per page) (updated)
• Lecture 6: Propositional calculus Slides Slides (2 per page) Slides (with solutions)
• Lecture 7: Propositional calculus II Slides Slides (2 per page) Slides (with solutions)
• Lecture 8: Predicate calculus Slides Slides (2 per page)
• Lecture 9: Expert systems Slides Slides (2 per page) Updated! The original definition of a definite clause on slide 5 was incorrect—a definite clause has a single positive literal, not negative.
• Lecture 10: Reasoning about actions I Slides Slides (2 per page)
• Lecture 11: Reasoning about actions II Slides Slides (2 per page)
• Lecture 12: Default reasoning Slides Slides (2 per page)
• Lectures 13 & 14: Reasoning with uncertainty Slides Slides (2 per page)
• Lecture 15: Learning Slides Slides (2 per page)
• Lecture 16: Decision trees Slides Slides (2 per page)

Assessment

Assessment is by means of a two-hour exam. Past papers are available from the Portal (click the Library tab and then the Exam Papers link under Library Searches). Papers for sessions prior to 2006-2007 are listed under the old G6DFAI module code. Note that, while the core topics are the same, the module syllabus changed slightly in the 2007-2008 session, and the 2007-2008 exam differs in scope and content from previous years. The 2008-2009 exam will be similar in style to the 2007-2008 exam.

If you have queries about the exam, you may find the feedback on the 2007/2008 paper helpful.

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Copyright © 2008 Brian Logan. Copyright © 2010 Neil Madden.

This file is maintained by Neil Madden

Last modified: 02-Feb-2010, 14:29