Syllabus - Schedule - CSG120 Artificial Intelligence - Spring 2006

Professor Futrelle

Version of 11 April 2006

Access the various official NU Calendars here. Access a handy non-NU calendar for the year 2006 here.

Your responsibilities are laid out below and in the Project, Assignments and Exam pages.

The material below is correlated with the two textbooks by Russell and Norvig, your "AIMA" and "PAIP" textbooks. It represents an approximate description of what will be presented as does not reflect the full details or schedule of what was actually presented. The alterations to the schedule below are primarily delays in the dates in which material was presented. The Uncertainty portions started and ended later and the Machine Learning portion ran to the end of the course.

Course part 1 - Search and Agents

Week 1. January 9th

Lecture 1A: Course overview (1) Survey (2) Topics (3) Procedures (4) Tools (5) Resources (6) Your course project (7) Student questionnaire (8) Downloading the textbook's code (9) Running Lisp on Solaris.

Reading and exercises: AIMA Ch. 1, PAIP Chs. 1, 2, 3 (Lisp review for some of you - hard work for others). See the Assignments page for guidance about the exercises and programming you should be doing along side your reading.

Lecture 1B: Lisp - Generate and parse natural language, PAIP Ch. 2, AIMA pgs. 790-800 and the *E0* grammar in the AIMA Lisp sources.

Assignment #0 Lisp startup, email signup.

No class, Monday, Jan 16th

Week 2. January 23rd

Lecture 2A: .
Basic search concepts; the search tools in PAIP Sec. 6.4. GPS overview from PAIP Chap. 4, but especially its treatment as a simple search problem in PAIP Sec. 6.5. AIMA, all of Chap. 3.

Lecture 2B: SHORT LISP QUIZ
Introduction to informed search. A* in PAIP Sec. 6.4 and AIMA, Chap. 4.

Assignment #1, due emailed by 11:59pm, January 26th. Hardcopy portions due in class Jan 30th.

Week 3. January 30th

Lecture 3A: Continued discussion of search, AIMA Chap. 3, but focusing on Chap. 4.

Lecture 3B: Constraint Satisfaction Problems (CSP). AIMA Chap. 5 and PAIP Ch. 17.

Course part 2 - Logic and Knowledge Representation

Week 4. February 6th

Lecture 4A: Propositional logic, tabular form. Resolution in propositional logic. AIMA Ch. 7.

Lecture 4B: First-order predicate logic and intro to knowledge representation. AIMA Ch. 8 and portions of Ch. 10.

Week 5. February 13th

Initial Project Plan, Proj1, due as hardcopy in class or in email by 11:59pm. Details here.

Lecture 5A: Resolution in first-order logic. AIMA Ch. 9. Otter as a full proof system.

Lecture 5B: Prolog. How it works, how to use it (SWI-Prolog) and Prolog in Lisp (PAIP). Strengths and weaknesses of Prolog. PAIP Ch. 14.
See the course information on Prolog, including our installed SWI-Prolog, and related topics and resources.

Assignment #2, due emailed by 11:59pm, February 23rd. Hardcopy portions due in class February 27th.

No class, Monday, Feb 20th

Course part 3 - Uncertainty

Week 6. February 27th

Lecture 6A: Knowledge Representation in more detail.

Lecture 6AB: Uncertain knowledge. Probability and intro to Bayes networks.

No class, Monday, March 6th (Spring break)

Week 7. March 13th

Lecture 7A: Bayesian inference.

Lecture 7B: Hidden Markov Models (HMM) and dynamic Bayes.

Assignment #3, due emailed by 11:59pm, March 16th. Hardcopy portions due in class March 20th.

Course part 4 - Learning

Week 8. March 20th

Interim Project, Proj2. You are to make a short class presentation in class today. Email your project by 11:59pm, March 21st. Details here.

Lecture 8A: Brief student presentations of their Interim Projects
Machine Learning. Attributes, training, testing. Perceptrons and their limitation. Decision trees. The WEKA tools.

Week 9. March 27th

Lecture 9A: Machine learning. Expectation maximization, neural nets, genetic algorithms, kernel methods. SVM^light.

Lecture 9B: Continue and finish machine learning.

Assignment #4, CANCELLED - No Assignment #4.

Course part 5 - CANCELLED - Was to be natural language.

Week 10. April 3rd

Lecture 10: MIDTERM EXAM.

Week 11. April 10th

Lecture 11A: Machine Learning

Lecture 11B: Machine Learning

No class, Monday, April 17th

Week 12. April 24th

Lecture 12A : Final project presentations.

Final Project, Proj3. You are to make a class presentation in class today, about five minutes duration. Email your Final Project by 11:59pm, April 25th. Details here.

Lecture 12B : Final lecture on machine learning.

Final Exam - a take-home exam, given out April 24th and due by 11:59pm, Friday, the 28th.

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