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: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%