# CS533 Applied Artificial Intelligence for Engineers Fall 2000

**Instructor**
Tom Dietterich, Dearborn 306, 737-5559, tgd@cs.orst.edu
Office Hours: To Be Determined.
**Text**
There will be no textbook. Class notes and photocopies of relevant
articles will be distributed in class.
**Grading** (**Late assignments are not accepted**)
Written Homework 30%
Programs 30%
Midterm 20%
Final 20%
**COURSE SCHEDULE**
Sep 25 Course Overview
**INTRODUCTION TO C++**
Sep 27 Introduction to C++; types, variables, I/O
29 C++ control structures; loops and loop escapes
Oct 2 C++ function definition, parameter passing, and return
4 C++ Classes and object-oriented programming
6 C++ class library: vector, list, heap. Iterators, Dynamic storage
9 C++ Tic/Tac/Toe program.
**STATE SPACE SEARCH**
11 Job shop scheduling.
13 Problem spaces. A constructive problem space for scheduling.
16 Problem space properties. Improving the problem space.
18 Repair-based problem space and simulated annealing
**RULE-BASED PROGRAMMING and DESIGN**
20 Introduction to design. Gearbox problem. Problem space.
23 Constraint analysis, constraint propagation, operators
25 More on constraint analysis.
27 Implementing generators, propagators, and testers via rules
30 More on rule implementation.
Nov 1 **MIDTERM EXAM**
**MACHINE LEARNING AND PATTERN RECOGNITION**
3 Introduction to machine learning
6 Neural networks and the backpropagation algorithm, overfitting
8 Stopped training, other strategies. ALVINN demo.
10 Decision tree algorithms
13 Reinforcement Learning (1)
15 Reinforcement Learning and Job Shop Scheduling
**BAYES NETWORKS AND DIAGNOSIS**
17 Bayes Networks: Basic ideas
20 Bayes Networks: Computing probabilities
22 Bayes Networks: Diagnosis (1)
24 THANKSGIVING HOLIDAY
27 Bayes Networks: Diagnosis (2)
29 Spare day 1
Dec 1 Spare day 2; Course Summary
4 **12:00 FINAL EXAM**