CS 430: Introduction to Artificial Intelligence
Fall 2005


Instructor: Weng-Keen Wong

Email: wong@eecs.oregonstate.edu
Office: 2075 Kelley
Office Hours: Tu 1:00-2:00, WF 2:00-3:00 or by appointment

TA: Chris Ventura

Email: ventura@eecs.oregonstate.edu
Office: KEC 1130
Office Hours: TTh 11:00-12:00 or by appointment

Syllabus


Announcements


Lectures

Date Slides Reading
Monday 9/26 Introduction 2pp or 6pp Chapter 1
Wednesday 9/28 Agents 2pp or 6pp Chapter 2
Friday 9/30 Uninformed Search 2pp or 6pp Sections 3.1-3.6
Monday 10/3 Informed Search 2pp or 6pp Sections 4.1-4.2
Wednesday 10/5 Local Search (Hillclimbing, Simulated Annealing) 2pp or 6pp Section 4.3
Friday 10/7 Local Search (Genetic Algorithms) 2pp or 6pp Section 4.3
Monday 10/10 Adversarial Search 2pp or 6pp , Alpha-Beta Pruning Exercise Section 6.1, 6.2, 6.3
Wednesday 10/12 Adversarial Search II 2pp or 6pp Section 6.4, 6.5, 6.6, 6.7
Friday 10/14 Game Theory I 2pp or 6pp Section 17.6
Monday 10/17 Game Theory II 2pp or 6pp Section 17.6
Wednesday 10/19 Game Theory III 2pp or 6pp Section 17.6
Friday 10/21 Game Theory IV 2pp or 6pp Section 17.6
Monday 10/24 Propositional Logic 2pp or 6pp Sections 7.1, 7.2, 7.3
Wednesday 10/26 Propositional Logic II 2pp or 6pp Sections 7.4, 7.5
Friday 10/28 First Order Logic 2pp or 6pp Sections 8.1, 8.2, 8.3
Monday 10/31 First Order Logic (notes from last time) and Uncertainty 2pp or 6pp Section 13.1
Wednesday 11/2 Midterm Review
Friday 11/4 Midterm
Monday 11/7 Probability 2pp or 6pp Section 13.2, 13.3, 13.4
Wednesday 11/9 Probability2 2pp or 6pp Section 13.5, 13.6, 14.1
Friday 11/11 Bayesian Networks (d-separation) 2pp or 6pp and Naive Bayes 2pp or 6pp Section 14.2
Monday 11/14 Bayesian Networks (Structure Learning) 2pp or 6pp Parts of 14.2 and 20.2
Wednesday 11/16 Bayesian Networks (Inference) 2pp or 6pp 14.4 (ignore Variable Elimination)
Friday 11/18 Markov Decision Processes 2pp or 6pp Sections 17.1-17.2
Monday 11/21 Markov Decision Processes II 2pp or 6pp Section 17.3
Wednesday 11/23 Reinforcement Learning 2pp or 6pp Sections 21.1, 21.2
Friday 11/25 Thanksgiving
Monday 11/28 Reinforcement Learning II 2pp or 6pp Sections 21.3 and Parts of 21.4
Wednesday 11/30 Special Topics
Friday 12/2 Exam Review


Written Assignments

Programming Assignments

Practice Exams

Midterm Solutions