| CSC 261 | Artificial Intelligence | Fall 2013 |
Note: Homework is shown in the assignment column on the day it is due (not the day assigned).
Note: Readings are RN="Russell & Norvig", LM="Lee & Mead", and ETJ="Jaynes". LM and ETJ may be found under the Documents section of the PioneerWeb for this course.
Important: With the exception of exam dates, this schedule is tentative,. Topics and activities for a subsequent class may be considered finalized by the end of the previous class. For example, Wednesday's reading is final immediately after Monday's class (because Tuesday is lab day).
Skip to week: 1 2 3 4 5 6 7 8 9 10 11 12 13 14 Final
| Week | Day | Date | Topic | Reading | Assignment |
|---|---|---|---|---|---|
| Fri | 8/30 | Introduction to AI | RN 1 pp. 1-30 | ||
| 1 | Mon | 9/2 | Intelligent Agents | RN 2.0-2.3 pp. 34-46 | Lab 0 |
| Tue | 9/3 | Lab: Recalling Scheme | Lab 1 | ||
| Wed | 9/4 | Agent Structure | RN 2.4-2.5 pp. 46-59 | ||
| Fri | 9/6 | Search | RN 3.0-3.3 pp. 64-81 | ||
| 2 | Mon | 9/9 | Uninformed Search | RN 3.4 pp. 81-91 | Lab 1 |
| Tue | 9/10 | Lab: Uninformed Search | Lab 2 | ||
| Wed | 9/11 | Informed Search | RN 3.5-3.5.2,3.6-3.7 pp. 92-99, 102-109 | ||
| Fri | 9/13 | Local Search | RN 4.0-4.2 pp. 120-132 (to "step size") | ||
| 3 | Mon | 9/16 | Nondeterministic Environments, Partial Observations | RN 4.3-4.4 pp. 133-146 | Lab 2 |
| Tue | 9/17 | Lab: Heuristic Search | Lab 3 | ||
| Wed | 9/18 | Online Search | RN 4.5-4.6 pp. 147-154 | ||
| Fri | 9/20 | Adversarial Search | RN 5.0-5.4.2, 5.9 pp. 161-176, 189-190 | ||
| 4 | Mon | 9/23 | Exam 1 | RN 2.0-4.6 | Lab 3 |
| Tue | 9/24 | Lab: Adversarial Search | Lab 4 | ||
| Wed | 9/25 | Propositional Logic | RN 7.0-7.4 pp. 234-249 | ||
| Fri | 9/27 | Propositional Inference | RN 7.5-7.5.2 pp. 249-256 | ||
| 5 | Mon | 9/30 | Propositional Inference: Chaining | RN 7.5.3-7.5.4, 7.8 pp. 256-259, 274-275 | Lab 4 |
| Tue | 10/1 | Lab: Propositional Logic | Lab 5 | ||
| Wed | 10/2 | First-Order Logic | RN 8.0-8.3, 8.5 pp. 285-306, 313 | ||
| Fri | 10/4 | FOL Inference | RN 9.0-9.3.2 pp. 322-333 | ||
| 6 | Mon | 10/7 | Backward Chaining and Prolog | RN 9.4-9.4.2, 9.4.4 pp. 337-342; LM pp. 1-11 Skip (or skim) RN 9.4.3 | Lab 5 |
| Tue | 10/8 | Lab: First-Order Logic | Lab 6 | ||
| Wed | 10/9 | Probability | ETJ 1.1-1.4, 1.7 pp. 1-6, 13-19; RN 13.0-13.3 pp. 480-494 | ||
| Fri | 10/11 | Independence and Bayes' Rule | RN 13.4-13.5, 13.7 pp. 494-499, 503 | ||
| 7 | Mon | 10/14 | Bayesian Learning | RN 18.0-18.2 pp. 693-697; ETJ 4 pp. 401-409 | Lab 6 |
| Tue | 10/15 | Bayesian Learning, cont. | ETJ 4, pp. 410-418 | ||
| Wed | 10/16 | Pause for Breath | |||
| Fri | 10/18 | Exam 2 | RN 5.0-13.3 | ||
| Enjoy Fall Break! | |||||
| 8 | Mon | 10/28 | Bayesian Networks | RN 14.0-14.2 pp. 510-518 | |
| Tue | 10/29 | Lab: Probability | Lab 7 | ||
| Wed | 10/30 | Bayes Net Inference | RN 14.4-14.4.2 pp. 522-528 | ||
| Fri | 11/1 | Dynamic Bayes Nets | RN 15.0-15.1 pp. 566-570 | ||
| 9 | Mon | 11/4 | DBN Inference | RN 15.2 pp. 570-578 | Lab 7 |
| Tue | 11/1 | Lab: Hidden Markov Models | Lab 8 | ||
| Wed | 11/2 | Pause for breath | |||
| Fri | 11/8 | Evaluating Hypotheses | RN 18.4.0, 18.4.2 pp. 708-709, 710-712 | ||
| 10 | Mon | 11/11 | Lab: Decision Trees | RN 18.3-18.3.4, pp. 697-704; Lab 9, Introduction & Background, pp. 1-5 | Lab 8 |
| Tue | 11/12 | Lab: Decision Trees | Lab 9 | ||
| Wed | 11/13 | Learning with Linear Models | RN 18.6-18.6.1, 18.6.3-18.6.4, pp. 717-720, 723-725 | ||
| Fri | 11/15 | Making Decisions | RN 16.0-16.3 pp. 610-621 | ||
| 11 | Mon | 11/18 | Decision Networks and Value of Information | RN 16.5-16.8 pp. 626-636 | Lab 9 |
| Tue | 11/19 | Lab: Decision Tree Analysis | Lab 10 | ||
| Wed | 11/20 | Pause for breath | |||
| Fri | 11/22 | Exam 3 | RN 13-15, 18; ETJ 1,4 | ||
| 12 | Mon | 11/25 | Markov Decision Processes | RN 17.1-17.2.2, 17.3 pp. 645-654, 656-658 | Lab 10 |
| Tue | 11/26 | Lab: Value Iteration | Lab 11 | ||
| Wed | 11/27 | No class | |||
| Fri | 11/29 | Thanksgiving Break | |||
| 13 | Mon | 12/2 | Passive Reinforcement Learning | RN 21.1-21.2 pp. 830-838 | Lab 11 |
| Tue | 12/3 | Lab: Policy Iteration and Passive RL | Lab 12 | ||
| Wed | 12/4 | Value Iteration in C | |||
| Fri | 12/6 | Active Reinforcement Learning | RN 21.3 839-845 | ||
| 14 | Mon | 12/9 | Building Watson | Ferrucci et al. | Lab 12 |
| Tue | 12/10 | Lab: Reinforcement Learning | Lab 13 | ||
| Wed | 12/11 | Philosophical Foundations | RN 26 pp. 1020-1040 | ||
| Fri | 12/13 | Wrap-Up | RN 27 pp. 1044-1052 | ||
| F | Fri | 12/20 | Final Exam (9 a.m.) | Lab 13 | |