Instructor: Mark Hasegawa-Johnson (jhasegaw -at- illinois.edu)
Office hours (2011 Beckman): Tuesdays and Thursdays 3:30-4:45PM or by appointment.
TAs:
Prerequisites: data structures (CS 225 or equivalent), algorithms highly desirable, basic calculus, familiarity with probability concepts a plus but not required.
Textbook: Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach, 3rd edition.
Grading scheme:
Date | Topic | Readings and assignments | Slides |
---|---|---|---|
August 23 | Intro to AI | Reading: Ch. 1 | lec01_intro |
August 25 | History and themes | Reading: Ch. 1 | lec02_history |
August 30 | Agents | Reading: Ch. 2 | lec03_agents |
September 1 | Search intro | Reading: Sec. 3.1-3.3 | lec04_search_intro |
September 6 | Uninformed search | Reading: Sec. 3.4 | lec05_uninformed_search |
September 8 | Informed search | Reading: Sec. 3.5-3.6 Homework: Assignment 1 is out |
lec06_informed_search |
September 13 | Lecture Cancelled | ||
September 15 | Constraint satisfaction problems | Reading: Ch. 6 | lec07_csp |
September 20 | Deterministic Games with Full Information | Reading: Ch. 5 | lec08_adversarial_search.pptx |
September 22 | Policy Classifiers and Value Regressors; Stochastic Games | Assignment 1 due September 26 | lec09_stochastic_games.pptx |
September 27 | Game theory | Reading: Sec. 17.5-17.6 | lec10_game_theory.pptx |
September 29 | Game theory cont. | Homework: Assignment 2 is out | |
October 4 | Planning | Reading: Ch. 10 | lec11_planning.pptx |
October 6 | Probability | Reading: Ch. 13 | lec12_probability.pptx |
October 11 | Midterm review | review, solutions | Exam 1 review |
October 13 | Midterm (in class) | ||
October 18 | Bayesian inference | Reading: Ch. 13 | lec13_bayesian_inference.pptx |
October 20 | Bayesian inference cont. | Assignment 2 due October 24 | lec13_bayesian_inference.pptx |
October 25 | Bayesian Networks | Homework: Assignment 3 is out | lec14_bayes_nets.pptx |
October 27 | Bayes Net Inference | Reading: Ch. 20 | lec15_bayes_net_inference.pptx |
November 1 | Hidden Markov Models | Reading: Ch. 15, 17 | lec16_hmm.pptx |
November 3 | Markov Decision Processes | Reading: Ch. 17 | lec17_mdp.pptx |
November 8 | Reinforcement Learning | Reading: Ch. 21 | lec18_rl.pptx |
November 10 | Machine Learning | Reading: Ch. 21 Assignment 3 due November 14 | lec19_ml_intro.pptx |
November 15 | Lecture Canceled | Homework: Assignment 4 is out | |
November 17 | Lecture Canceled | ||
November 29 | Neural networks and support vector machines | lec20_nn_and_svm.pptx | |
December 1 | Deep learning | Assignment 4 due December 5 | lec21_cnn.pptx |
December 6 | Final review | review problems. | |
December 9, 14:00-15:15, Siebel 0216 | Exam 2 |