CS 540 Section 1: Introduction to Artificial Intelligence
Fall 2011
Lectures: MWF 9:55am - 10:45am, Computer Science 1325
Discussions via piazza (need a wisc.edu email address to sign up)
Homeworks
Examinations
Topics (Reading)
Unit 0: Introduction (lecture notes, ch 1, 2)
AI: history and today, Turing test.
Anti-AI: Captcha and the ESP game
Unit 1: Machine Learning
Clustering (lecture notes, Z&G ch 1)
Classification
k-Nearest-Neighbor classifier
Decision trees (lecture notes, 18.1-18.3)
Support Vector Machines (lecture notes, short tutorial, long tutorial)
Neural networks (lecture notes, 18.7)
Probability and statistics basics (lecture notes, 14.1, 14.2, 14.4)
Bayesian networks (lecture notes, Charniak tutorial, Bishop PRML 8.2 for D-separation)
Speech recognition (lecture notes, 15.1-15.3, 23.5, HMM tutorial)
Guest lecture: Bryan Gibson on Co-Training
Unit 2: Search
Uninformed search (lecture notes, ch 3)
Breadth-first search, uniform-cost search, depth-first search, iterative-deepening
Informed search (lecture notes, ch 3)
A* algorithm
Search as optimization
Hill-climbing, Simulated annealing, genetic algorithms (lecture notes, 4.1)
Continuous optimization (lecture notes, 4.2)
Constraint satisfaction (lecture notes, 6.1-6.3)
Game playing
Minimax, alpha-beta pruning (lecture notes, 5.1 - 5.3)
Game theory (lecture notes, 17.5 - 17.6)
Unit 3: Logic
Propositional logic (lecture notes, 7.1, 7.3 - 7.5)
First-Order Logic (lecture notes, 8.1 - 8.3)
Deductive inference, unification, forward and backward chaining, resolution ((lecture notes, 9)
Instructor: Xiaojin (Jerry) Zhu, Associate Professor in Computer Sciences
Office Hours: Thursdays 3-4pm in 6391 Computer Sciences, or by appointment
E-mail: jerryzhu@cs.wisc.edu
Phone: 608-890-0129
Teaching Assistants: Madhu Ramanathan (madhurm@cs.wisc.edu)
Office hour : Friday 11.30AM - 12.30PM
Phone : 608-262-6601
Office number : 1306
Prerequisite: CS 367
Textbook:
Artificial Intelligence: A Modern Approach, 3rd edition (blue cover, not green).
Stuart J. Russell and Peter Norvig. Prentice Hall, Englewook Cliffs, N.J., 2010
Grading:
- Midterm Exam: about 30%
- Final Exam: about 30%
- Homework Assignments: about 40%
Note: The distribution of CS540 final grades has been as follows.
This is an approximation, and changes from semester to semester.
The median student's course grade is usually a low B or high BC.
The percentiles refer to ranking based on the final weighted score.
A top ~25% of class
AB next ~15%
B next ~25%
BC next ~20%
C next ~10%
D next ~3%
F next ~2%