COMP3702/COMP7702 Web page

Artificial Intelligence (Semester 2, 2009)

Course Coordinator 2009: Ruth Schulz.

 

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

            Office Hours: Tuesday 2-3 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 (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 10.00-11.50am 78-343	Reading Russell and Norvig, 2003	Tutorial Session Tues 12.00-1.50pm 68-214 Wed 10.00-11.50am 14-115 Fri 10.00-11.50am 78-420	Assessment
					Note: Maximum 2 per group for tutorial sessions. If tutorials are submitted online, they must be submitted by 5pm on the Monday before the tutorial session.
1	27 July	1	COMP3702 / COMP7702 Introduction to artificial intelligence, an agent-based perspective	Chapters 1, 2 and 26: pp. 947-949, 958-960.	No tutorial
2	3 August	2	Solving problems by searching	Chapter 3	The definition of artificial intelligence (solutions/hints)
3	10 August	3	Informed search and exploration	Chapter 4 (except 4.4 and 4.5)	Problem Representation (solutions/hints)	Assignment 1 (available now)
4	17 August	4	Adversarial search, game playing	Chapter 6	Informed Search (solutions/hints)
5	24 August	5	Review and Applications, Discussion of Assignment 1		Adversarial search (solutions/hints)
6	31 August	6	Mid-semester exam		Assignment 1 preparation	Mid-semester exam (optional for COMP3702) will be multiple choice, 50 mins. (Closed book)
7	7 September	7	Probabilistic reasoning	Chapter 13 + 7.1-7.2	Exam discussion, Feedback and revision of tutorials 1-4	Assignment 1 deadline (Friday 11th September, 5pm)
8	14 September	8	Principles of machine learning	Chapters 18 and 19	Probabilistic reasoning (solutions/hints)	Assignment 2 (available now)
9	21 September	9	Symbolic machine learning techniques, Discussion of Assignment 2	Chapters 18 and 19	Machine learning basics (solutions/hints)
	28 September	Mid-semester break (one week)
10	5 October	10	Statistical machine learning,  Neural networks intro	Chapter 20 (20.1-20.2) (20.5)	Current best learning and decision trees (solutions/hints)
11	12 October	11	Neural networks	Chapter 20 (20.5-onwards)	Decision Trees and Naïve Bayes Classification (solutions/hints)
12	19 October	12	Applications of AI i. Developmental Robotics (Dr Scott Bolland) ii. Robotics (Dr Ruth Schulz)	Chapter 25	Neural networks (solutions/hints) Assignment 2 preparation	Assignment 2 deadline (Friday 23rd October, 5pm)
Revision Week 13	26 October	13	Assignment 2 Competition, Review		Robotics (solutions/hints)
	2 November	Revision Period
Exam Week 1	9 November					Final Exam 2:30pm, Monday 16 November, St Leo’s College Boardroom
Exam Week 2	16 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)(0 marks OR 10 marks)
• Final examination (60 marks OR 50 marks)
• (best result of the including or not including the mid-semester results; total exam contribution is 60 marks)
• Two assignments (30 marks)
• Ten tutorials (10 marks)

COMP7702 will be assessed by a 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 (10 marks)
• Final examination (50 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.