1. G5BAIM Artificial Intelligence Methods
Dr. Graham Kendall
Course Introduction

2. You are a caveman (or woman)
I travel back in time and bring you a Pentium III PC and show you some of the things it is capable of doing.
Question : Would you, as a caveman, consider the computer to be intelligent?
Hands up if you think the computer is intelligent?

3. Now we are in the present day
I show you the same Pentium III PC and show you some of the things it is capable of doing.
Question : Would you, as a computer science student, consider the computer to be intelligent?
Hands up if you now think the computer is intelligent?

4. We are still in the present day, but we are at the end of this lecture course.
Just before I leave the final lecture, I peel away my face and reveal I am an android. As an android I have just delivered a 24 hour lecture course and answered all your questions.
Question : Would you, as a computer science student, consider me to be intelligent?
Hands up if you think I am intelligent?

5. Second / Third Year Projects
Course Introduction
Course
Artificial Intelligence Methods
Lecturer
Graham Kendall
Room C80 (by appointment)
Web Page
Second / Third Year Projects

6. Course Introduction Last Years Course Good Points Bad Points
Handouts/Notes
Summary of Each Lecture
Willingness to Answer Questions
Bad Points
Speak Properly (Louder, Clearer, Faster, Slower)
Did Not Summarise Lectures
More Coursework Needed
Course content was too much / too little

7. Lecture Times and Locations
Course Introduction
Lectures
20 (ish)
Lecture Times and Locations
Monday 09:00 (LT2)
Thursday 15:00 (LT2)
Assessment
25% Coursework
75% examination (2 hours) - 4 Questions from 6

8. Aims of the Course
Define what we mean by AI (or at least give us a working definition for this course)
Write “AI” programs that
Explore search spaces using both blind, heuristic, meta- heuristic and evolutionary search techniques
Implement Neural Networks
Consider what is meant by artificial life and write programs that can learn
Consider ways of representing and using knowledge

9. Aims of the Course
This is very much a practical course. Although we will touch upon the philosophical issues we will not dwell on this area of AI.
This course is more concerned with writing useful AI programs than discussing if a computer is intelligent or not.

10. (Web site has an amazon link)
Textbooks
Artificial Intelligence – A Modern Approach (AIMA) (Russell/Norvig)
Much of the material for this course is from this book. If you are going to buy a book, then get this one.
(Web site has an amazon link)

11. Artificial Intelligence (Rich/Knight)
Textbooks
Artificial Intelligence (Rich/Knight)
This used to be the “standard” AI text book but AIMA is now taking its place – in my view

12. Artificial Intelligence (Winston)
Textbooks
Artificial Intelligence (Winston)
As for Rich/Knight

13. Textbooks
Artificial intelligence : Structure and Strategies for Complex Problem Solving (Luger/Stubblefield)

14. Computational Intelligence (Poole/Mackworth/Goebel)
Textbooks
Computational Intelligence (Poole/Mackworth/Goebel)
As good as AIMA but came out later

15. Useful Reading
The Essence of Artificial Intelligence (Cawsey)

16. Useful Reading
Seven Methods for Transforming Corporate Data into Business Intelligence (Dahr/Stein)

17. Useful Reading
Artificial Intelligence and Computer Games (Richard Bartle)

18. Useful Reading
Computer Gamesmanship (David Levy)

19. Neural Networks
The Essence of Neural Networks (Callan)

20. Neural Networks
Neural Network (Davalo)

21. Neural Networks
Fundamentals of Neural networks (Fausett)

22. Proposed Lecture and Coursework Schedule
Introduction
Lectures 1, 2 & 3
Course Introduction and Brief History of AI
Searching
Lectures 4 & 5
Search problems, their implementation and how to evaluate
Lectures 6 & 7
Blind Searches

23. Proposed Lecture and Coursework Schedule
Heuristic Searches
Lectures 8, 9 & 10

24. Proposed Lecture and Coursework Schedule
Revision
Lecture 11
Modern Heuristic Search Methods
Lectures 12, 13, 14, 15, 16 & 17
E.g. Genetic Algorithms, Ant Algorithms, Simulated Annealing, Tabu Search, Constraint Satisfaction
Neural Networks
Lectures 18 & 19

25. Proposed Lecture and Coursework Schedule
Revision
Lecture 20
Maybe something on Artificial Life

26. Proposed Lecture and Coursework Schedule
Handed out in the next week
Definitely a programming assignment
You will need to write a report (max five pages) - 16%
You will need to test your program against three others chosen randomly from the group - 9%
Coursework will be administered by a Teaching Assistant
Closing date yet to be decided

27. Proposed Lecture and Coursework Schedule
Guest Lecture
Possibly a guest lecturer giving six lectures
Possibly on Genetic Algorithms
May need to take the Operating System lecture slots
May need to add a couple of extra lectures

28. Are these AI??
Boids

29. Course Introduction Finished Now the hard work starts