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G5AIAI Introduction to Artificial Intelligence. Course Introduction. Graham Kendall. You are a caveman (or woman) I travel back in time and bring you a Pentium IV PC and show you some of the things it is capable of doing.

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g5aiai introduction to artificial intelligence

G5AIAIIntroduction to Artificial Intelligence

Course Introduction

Graham Kendall

slide2
You are a caveman (or woman)
  • I travel back in time and bring you a Pentium IV 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?
slide3
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?
slide4
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?
course introduction
Course Introduction
  • Course
    • Introduction to Artificial Intelligence
  • Lecturer
    • Graham Kendall
    • GXK@CS.NOTT.AC.UK
course introduction6
Course Introduction
  • Web Page
    • http://www.cs.nott.ac.uk/~gxk/courses/g5aiai/
  • EMAIL
  • Second / Third Year Projects
course context
Course Context

G5AIAI

Introduction to AI

G5BAIP Artificial Intelligence Programming

G5BAIM

Artificial Intelligence Methods

D53DIA Designing Intelligent Agents

who can attend this year
Who Can Attend? (This year)
  • Introduction to AI
    • First/Second Year Option
  • Artificial Intelligence Methods
    • Second/Third Year Option
course introduction9
Course Introduction
  • Last Years Course
    • Good 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
      • Feedback on Coursework Needed
      • Course content was too much / too little
course introduction10
Course Introduction
  • Lectures
    • 15 (ish)
  • Lecture Times and Locations
    • Monday 13:00 (CTF-LT2)
    • Friday 11:00 (CTF-LT3)
  • Assessment
    • 25% Coursework
    • 75% examination (2 hours)
aims of the course
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 and heuristic search techniques
    • Implement Neural Networks (perceptron)
aims of the course12
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.
textbooks
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)

textbooks14
Textbooks
  • Artificial Intelligence (Rich/Knight)
    • This used to be the “standard” AI text book but AIMA is now taking its place – in my view
textbooks15
Textbooks
  • Artificial Intelligence (Winston)
    • As for Rich/Knight
textbooks16
Textbooks
  • Artificial intelligence : Structure and Strategies for Complex Problem Solving (Luger/Stubblefield)
textbooks17
Textbooks
  • Computational Intelligence (Poole/Mackworth/Goebel)
    • As good as AIMA but came out later
useful reading
Useful Reading
  • The Essence of Artificial Intelligence (Cawsey)
useful reading19
Useful Reading
  • Seven Methods for Transforming Corporate Data into Business Intelligence (Dahr/Stein)
useful reading20
Useful Reading
  • Artificial Intelligence and Computer Games (Richard Bartle)
useful reading21
Useful Reading
  • Computer Gamesmanship (David Levy)
neural networks
Neural Networks
  • The Essence of Neural Networks (Callan)
neural networks23
Neural Networks
  • Neural Network (Davalo)
neural networks24
Neural Networks
  • Fundamentals of Neural networks (Fausett)
coursework schedule
Coursework Schedule
  • Coursework
    • Is already available
    • It does involve programming
    • Closing date is 4th December, but with an automatic weeks extension!
    • No further extensions
examinations
Examinations
  • Examination Rubric
    • You are expected to answer one of the two questions from section A and three of the five questions from section B.