Course syllabus

Formalities

Course programme: EDA132.

The course textbook is Artificial Intelligence: A Modern Approach, 3/e, by Stuart Russell and Peter Norvig, ISBN-10: 0132071487.

The course will be given in English.

Exams will be held on 25th of May 2012 and on 23rd of August 2012. Location and times can be found elsewhere.

This year's course will be given by Jacek Malec, Elin Anna Topp and Pierre Nugues. Jacek Malec is officially responsible for the course (kursansvarig). The contact info can be found on each teacher's home page. The mail address for assignment-related matters is tai snabela cs.lth.se (ask a Swede for an explanation). Other matters should be addressed directly to one of the teachers.

In the description below the teachers are denoted by the following acronyms:

• EAT - Elin Anna Topp
• JM - Jacek Malec
• PN - Pierre Nugues

Lectures

Date	No.	Lecture	Who	AIMA chapter	Note
19/1	1	Introduction. Agents.	JM	1, 2
26/1	2	Search 1	JM	3, 1/2 of 4
2/2	3	Constraint Satisfaction	JM	6
9/2	4	Search 2	JM	1/2 of 4, 5
16/2	5	Logic. Deduction	JM	7, 8, 1/2 of 9
23/2	6	Knowledge Representation	JM	12
24/2	7	Knowledge-Based Systems	guest		Friday!
1/3	8	Planning 1	JM	10
15/3	9	Planning 2	JM	11
22/3	11	Machine learning 1	PN	1/2 of 18	Order changed!
29/3	12	Machine Learning 2	PN	1/2 of 18	Order changed!
19/4	10	Probabilistic representation	EAT	13, 1/2 of 14	Order changed!
26/4	13	Machine Learning 3: reinforcement	EAT	21
2/5	14	NLP 1	PN	22	Wednesday!
3/5	15	NLP2	PN	23
10/5	16	Robotics	EAT	25
25/5		Exam		All :-)	8-13, Vic1:D
23/8		Re-exam		All :-)	14-19, E:3315

Programming Assignments

For details please see the programming assignments page.

No.	Date	Date	Topic	Who
	announced	due
1a	2/2	23/2	Constraint Satisfaction	JM
1b	9/2	23/2	Genetic Algorithms	JM
2a	1/3	29/3	Semantic Web	JM
2b	15/3	19/4	Planning	JM
3a	22/3	26/4	Decision Trees	PN
3b	29/3	3/5	Logistic Regression	PN
3c	26/4	10/5	Reinforcement Learning	EAT
4	3/5	21/5	NLP	PN

Reading Advice

Below you will find a list of the chapters in the textbook, and also other material, that we expect you to get acquainted with before the exam.

Please note that this has been updated to the 3rd edition. I will appreciate all feedback.

Besides, some sections may get excluded from the list below. Some additional material from the teachers may get added to the list.

• Introduction: Chapters 1 and 2,
• Search: Chapter 3, 4 and 5,
• Constraint Satisfaction: Chapter 6,
• Logic and Knowledge Representation: Chapter 7, 8 and 9,
• Knowledge-Based Systems: Chapter 12,
• Planning: Chapters 10 and 11,
• Probabilistic Knowledge: Chapters 13 and 14,
• Introduction to Machine Learning: Chapters 18 and 21,
• Natural Language Processing, Chapters 22 and 23,
• Robotics, Chapter 25.

Just for orientation, here are three pdf files with 2005, 2008 and 2011 exam questions. Enjoy! However, there will be no "suggested answers", "facit" or any other texts of this kind. Sorry.

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