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 COMP3702/COMP7702 Course Information 2008

Information from 2008

COMP3702/COMP7702 Web page

Artificial Intelligence (Semester 2, 2008)

Course Coordinator 2008: Janet Wiles.

 

Lecturers:

            Shoaib Sehgal (Email: First dot LastName AT imb "dot" uq "dot" edu "dot" au)

 

            Ruth Schulz (FirstName AT itee "dot" uq "dot" edu "dot" au)

            Office Hours: Tuesday 4-5 PM, Room 308, Axon building ITEE

Rationale

This course describes and discusses several algorithms and techniques within the fields of artificial intelligence and machine learning that have found theoretical or practical applicability in software design and engineering. Theoretical and practical understanding in these areas equips the student with the insights and tools required for solving complex and difficult problems, and for implementing them in software. Specific topics include problem solving by search, knowledge representation and inference, probabilistic reasoning, machine learning and information retrieval.

This course is aimed at students with a computer science/engineering background, with an interest in data structures and computing algorithms, and an aptitude for realising theoretical ideas in software.

Course Profiles: Comp3702 and Comp7702

Material

Russell S. and Norvig P., Artificial Intelligence: A modern approach, 2nd ed., 2003. Prentice Hall. Reading material supporting lectures as specified under "Reading" below.

Lecture slides are provided in a 6-per-page or 2-per-page format (links in the Teaching plan below).

Announcements

Announcements are regularly updated, to see latest course announcements click here.

Useful Links

Java for C++ programmers

Java for C and C++ programmers

Week Number

 

Monday's Date

 

Lecture Number

 

Lecture

Tues 2-4pm

Reading

Russell and Norvig, 2003

Tutorial Session

1. Tues 12-2pm, 2. Thurs 8-10am, 3. Thurs 12-2pm

Assessment

 

Part 1

 

 

Shoaib Sehgal

 

Note: Maximum 2 persons per group are allowed for tutorial sessions.

 

1

21 July

1

Introduction to artificial intelligence, an agent-based perspective

Chapters 1, 2 and 26: pp. 947-949, 958-960.

No tutorial

 

2

28 July

2

Solving problems by searching

Chapter 3

The definition of artificial intelligence

(solutions/hints)

 Assignment 1

(Available NOW)

3

4 August

3

Informed search and exploration

Chapter 4 (except 4.4 and 4.5)

Problem Representation

(solutions/hints)

 

4

11 August

4

Adversarial search, game playing

Chapter 6

Informed Search

(solutions/hints)

 

5

18 August

5

i- Introduction to Developmental Robotics – (Dr Scott Bolland)

ii- Applications of AI (Dr Shoaib Sehgal)

 

Adversarial search

(solutions/hints)

 

6

25 August

6

Mid-semester exam;

Discussion of assignment 1, related theory

 

Assignment 1 preparation

Mid-semester exam (optional) will be multiple choice, 20 questions, 45 mins. (Closed book) (details)

Part 2

 

 

Ruth Schulz

 

 

 

7

1 September

7

Probabilistic reasoning

Chapter 13 + 7.1-7.2

Feed Back and revision (30 Mins each on Tute 1-4)

Assignment 1 deadline (Friday 5th September, 5pm) [Note change of date]

[Also note change in submission requirements]

8

8 September

8

Principles of machine learning

Chapters 18 and 19

Probabilistic reasoning

(solutions/hints)

Assignment 2 available

(slides from lecture)

9

15 September

9

Symbolic machine learning techniques

Chapters 18 and 19

Machine learning basics

(solutions/hints)

 

10

22 September

10

Statistical machine learning 

Neural networks intro

Chapter 20 (20.1-20.2)

(20.5)

Current best learning and decision trees

(solutions/hints)

 

 

29 September

Mid-semester break (one week)

11

6 October

11

Neural networks

Chapter 20 (20.5-onwards)

Decision Trees and Naïve Bayes Classification

(solutions/hints)

 

12

13 October

12

Robotics

Chapter 25

Neural networks

(solutions/hints)
Assignment 2 preparation

 

Revision Week

13

20 October

13

Assignment 2 Competition, Review

 

Robotics

(solutions/hints)

Assignment 2 deadline (Friday 24th October 5pm)

 

27 October

Revision Period

Exam Week 1

3 November

 

 

 

 

Final Exam

Exam Week 2

10 November

 

 

 

 

Note: The slides are by no means final and subject to change before lecture.

Assessment

COMP3702 will be assessed by an optional mid-semester exam, a final exam and assignments. Your final grade (on a 1 to 7 scale) will be determined by combining the marks from the assessment components below.

  • Mid-Semester exam (optional – 10 marks)
  • Final examination (best of the mid-semester or final exam; total exam contribution is 60 marks)
  • Two assignments (30 marks)
  • Ten tutorials (10 marks)

COMP7702 will be assessed by an optional mid-semester exam, a final exam and assignments. Your final grade (on a 1 to 7 scale) will be determined by combining the marks from the assessment components below.

  • Mid-Semester exam (optional – 10 marks)
  • Final examination (best of the mid-semester or final exam; total exam contribution is 60 marks)
  • Two assignments (30 marks)
  • Ten tutorials (10 marks)

The examination papers for COMP3702 and COMP7702 are different. Assessment is described in detail in the course profile.