A survey of the basic concepts and techniques of Artificial Intelligence including Problem Solving, Knowledge Representation, Planning, Learning, and Natural Language Processing.
Upon completion of this course, you should be able to:
Nathalie Japkowicz, Office: DL 250, Office Hours: Tuesdays 11-1
Huaxing Wu, Office DL 474, Office Hours Tuesdays-Thursdays 1:30-2:30
Tuesdays and Thursdays, 9:30-10:45, Dreese Labs, 280
Homework assignments are due at the beginning of a class period. There will be no make-up on homeworks. Four homeworks are scheduled for the class at the following dates:
Week | Topic | Readings |
---|---|---|
1 | What is Artificial Intelligence? | Chapter 1 | Problem Representation | Section 4.1 |
2 | Blind Search | Sections 4.2 |
Heuristic Search | Section 4.3 | |
Assignment # 1: Problem Solving and Search | Due: January 26 | |
3 | Optimization and Search | Section 4.4 |
Adversarial Search | Section 4.5 | |
4 | Adversarial Search (Cont'd) | Section 4.5 |
Propositional Logic | Sections 3.1 and 3.2 | |
Assignment # 2: Adversarial Search and Knowledge Representation | Due: February 9 | |
5 | Predicate Calculus | Section 3.4 |
Midterm Review | ||
6 | Midterm | |
Resolution Proof | Sections 3.5 and 3.6 | |
Assignment # 3: Decision Tree Learning | Due: February 23 | |
7 | Resolution Proof (Cont'd) | Sections 3.5 and 3.6 | Deductive Retrieval Systems | Section 3.8 |
8 | Learning Overview, Theory, and Version Spaces | Sections 5.1,5.2, 5.3 |
Decision Trees and Neural Networks | Sections 5.4 and 5.5 | |
Assignment # 4: Natural Language Processing | Due: March 9 | |
9 | Natural Language Processing: Syntax | Sections 10.1, 10.2, 10.3 |
Natural Language Processing: Semantics and Pragmatics | Sections 10.4 and 10.5 | |
10 | Planning | Sections 7.1,7.2, 7.3 |
Final Review | ||
Final Exam | Check Master Schedule |