CS 371
Introduction to Artificial Intelligence Syllabus |
Date | Topics | Readings |
Tu 8/29 | Introduction, "What is AI?", agents, agent architectures, and environments | Ch. 1,2, Deep Blue article |
Th 8/31 | Search I: search problem formulation, uninformed search, breadth-first search, depth-first search, iterative deepening | Ch. 3, David's TripleCross Page |
Tu 9/5 | Search II: informed search, heuristic functions, best-first search, A* | Ch. 4 (skip SMA*) |
Th 9/7 | Search III: informed search, IDA*, iterative improvement, hill-climbing, simulated annealing (SA), genetic algorithms | |
Tu 9/12 | Search IV: constraint satisfaction, problem formulations, examples | Kumar CSP Survey (p.1-6), Dechter Constraint Networks (sections 1-2), Numerical Recipes in C SA excerpts (photocopy) |
Th 9/14 | Search V: constraint satisfaction (cont.), overview of techniques | |
Tu 9/19 | KR&R I: propositional logic, definitions/terminology, 3SAT as backtracking search, Davis-Putnam procedure | Ch. 6 |
Th 9/21 | KR&R II: 3SAT as stochastic, local optimization, GSAT, WALKSAT | Selman, Kautz, and Cohen Local Search Paper |
Tu 9/26 | KR&R III: computational complexity and phase transitions | Mitchell, Selman, and Levesque Hard/Easy SAT Problem Paper |
Th 9/28 | KR&R IV: first-order logic | Ch. 7 |
Tu 10/3 | KR&R V: first-order logic theorem proving | Ch. 9 |
Th 10/5 | Planning I | Ch. 11 |
Th 10/12 | Planning II | Ch. 12 |
Tu 10/17 | Planning III | |
Th 10/19 | Uncertainty I | Ch. 14 |
Tu 10/24 | Uncertainty II | Ch. 15 |
Th 10/26 | Uncertainty III | |
Tu 10/31 | Learning I | Ch. 18 |
Th 11/2 | Learning II | Ch. 19 |
Tu 11/7 | Learning III | Ch. 20 |
Th 11/9 | Learning IV | |
Tu 11/14 | Robotics I | Ch. 25 |
Th 11/16 | Robotics II | |
Tu 11/21 | Vision I | Ch. 24 |
Tu 11/28 | Vision II | |
Th 11/30 | Natural Language Processing | Ch. 22 |
Tu 12/5 | Philosophical Foundations | Ch. 26 |
Th 12/7 | AI: Present and Future | Ch. 27 |