6.825 | Fall 2002 | Graduate

# Techniques in Artificial Intelligence (SMA 5504)

## Calendar

Day # Topics Readings Lectures Exercises Assignments
1 Introduction AIMA 1, 2 Lec 1
2 Search: A*, Stochastic Methods AIMA 3, 4 Lec 2
3 Propositional Logic: Syntax, Semantics AIMA 6 Lec 3 Exercises, Lec 3-5
4 Propositional Satisfiability Finding Hard Instances of the Satisfiability Problem: A Survey Lec 4 PDF - 1.2 MB)   HW-1a Out
5 First-Order Logic: Intro AIMA 7.1 - 7.3 Lec 5 Solutions, Lec 3-5
6 FOL: Knowledge Representation
7 FOL: Resolution AIMA 9.6-9.7 Lec 7 Exercises, Lec 7-8
8 FOL: More Resolution Nilsson Chapter Lec 8 Solutions, Lec 7-8 HW-1b Out
HW-1a Due
9 Equality; Other Logics AIMA 8.6 Lec 9 Resolution & Paramodulation Exercises

Solutions

10 Planning: Situation Calculus and POP AIMA 7.4 - 7.10, 11
Programs with Common Sense
Lec 10
11 Planning: More POP   Lec 11 Exercise Solutions
12         HW-1b Due
HW-1c Out
13 Planning: GraphPlan and SATPlan Recent Advances in AI Planning, Weld, 1-2.2, 3.1; AIMA 13 Lec 12
14 Planning
Review Session
Lec 13
15 Probability AIMA 14 Lec 14 Exercise Solutions HW-1c Due
16 Quiz   Midterm Solutions Practice Midterm

Practice Solutions

17 Bayesian Networks AIMA 15.1-15.3 Lec 15
18 Bayesian Networks: General Inference AIMA Second Edition 14 Lec 16 Exercise Solutions (15-16)
19 Learning: Bayes Nets: Observable Nilsson Chapter Lec 17 Exercise Solutions 17 HW 2a Out
20 Learning: Bayes Nets: Hidden   Lec 18 Exercise Solutions 18
21 Decision Theory AIMA 16 Lec 19 Exercise Solutions 19
22 Markov Decision Processes AIMA 17 Lec 20
23 Probabilistic Planning Optional: Probabilistic Planning in the Graphplan Framework
24 Reinforcement Learning AIMA 20 Lec 22   HW-2a Due
HW-2b Out
25 Supervised Learning AIMA 18.1-18.4, 19.1-19.5     HW-3 Out (Not Graded)
26 Philosophy AIMA 26
27 Review       HW-3 Solutions
28 Final Exam
Time: 3 Hours

## Course Info

Fall 2002
##### Learning Resource Types
Lecture Notes
Programming Assignments