ECE 469: Artificial Intelligence
Fall 2020
Tuesday 5:00 PM - 6:00 PM,
Wednesday 11:00 AM - 1:00 PM
Lectures will be held remotely using Teams
Instructor:
Carl Sable
e-mail: carl.sable@cooper.edu
Office: Room 614
"Artificial Intelligence: A Modern Approach"
(3rd edition or 4th edition)
by Stuart Russell and Peter Norvig
The book is recommended, not required.
The book has a nice
associated website.
Project 1: 33 1/3%
Project 2: 33 1/3%
Three problem sets: 33 1/3%
Projects and problem sets will be posted when they are assigned.
The schedule will be updated as the semester progresses. All dates
which have not yet occurred should be considered tentative!
Part 1: Introductory Concepts
- Tuesday, September 1
Topic: Course Introduction
Suggested Reading: R&N Ed. 3 or 4, Chapter 1
- Wednesday, September 2
Introduction (continued)
Topic: Intelligent Agents
Suggested Reading: R&N Ed. 3 or 4, Chapter 2
Part II: Search and Games
- Tuesday, September 8
Topic: Simple Search Strategies
Suggested Reading: R&N Ed. 3 or 4, Sections 3.1 - 3.4 and 4.4.1
- Wednesday, September 11
Simple Search Strategies (continued)
- Tuesday, September 15
Simple Search Strategies (continued)
Topic: Advanced Search Strategies
Suggested Reading: R&N Ed. 3 or 4, Sections 3.5 - 3.6, 4.1 - 4.2,
and 4.5
- Wednesday, September 16
Advanced Search Strategies (continued)
- Tuesday, September 22
Advanced Search Strategies (continued)
Topic: Games
Suggested Reading: R&N Ed. 3 or 4, Chapter 5
- Wednesday, September 23
Games (continued)
- Tuesday, September 29
Games (continued)
- Wednesday, September 30
Games (continued)
- Tuesday, October 6
Project #1 assigned and discussed
Part III: Dealing with Uncertainty
- Wednesday, October 7
Topic: Probability
Suggested Reading: R&N Ed. 3, Chapter 13 or Ed. 4, Chapter 12
- Tuesday, October 13
Topic: Bayesian Networks
Suggested Reading: R&N Ed. 3, Chapter 14 or Ed. 4, Chapter 13
- Wednesday, October 14
Topic: Bayesian Networks (continued)
- Tuesday, October 20
Topic: Hidden Markov Models
Suggested Reading: R&N Ed. 3, Sections 15.1 - 15.3
or Ed. 4, Sections 14.1 - 14.3; and
"An
Introduction to Hidden Markov Models and Bayesian Networks"
(Ghahramani 2001)
Part IV: Machine Learning
- Wednesday, October 21
Topic: Machine Learning Concepts
Suggested Reading: R&N Ed. 3, Sections 18.1 - 18.2 and 18.4
or Ed. 4, Sections 19.1 - 19.2 and 19.4
Topic: Decision Trees
Suggested Reading: R&N Ed. 3, Section 18.3 or Ed. 4, Section 19.3
- Tuesday, October 27
Decision Trees (continued)
- Wednesday, October 28
Topic: Bayesian Learning
Suggested Reading: R&N Ed. 3 or 4, Chapter 20
- Tuesday, November 3
Topic: Feedforward Neural Networks
Suggested Reading: R&N Ed. 3, Section 18.7
or Ed. 4, Sections 21.1 - 21.2
Click here
for my annotated version of Figure 18.24
- Wednesday, November 4
Feedforward Neural Networks (continued)
- Tuesday, November 10
Topic: Deep Neural Networks
Suggested Reading: R&N Ed. 4, Sections 21.3 and 21.5
(this topic is not covered in Ed. 3)
- Wednesday, November 11
Project #2 assigned and discussed
Topic: Non-parametric Machine Learning
Suggested Reading: R&N Ed. 3, Sections 18.8 - 18.9
or Ed. 4, Sections 19.7.1 and 19.7.5 - 19.7.6
Part V: Natural Language Processing
- Tuesday, November 17
Topic: Conventional Statistical Natural Language Processing
Suggested Reading: R&N Ed. 3, Chapter 22 or Ed. 4, Section 23.1
- Wednesday, November 18
Conventional, Statistical Natural Language Processing (continued)
- Tuesday, December 1
Topic: Conventional Computational Linguistics
Suggested Reading: R&N Ed. 3, Chapter 23
or Ed. 4, Sections 23.2 - 23.6
- Wednesday, December 2
Natural Languages (continued)
- Tuesday, December 8
Topic: Deep Learning and NLP
Suggested Reading: R&N Ed. 4, Chapter 24
(this topic is not covered in Ed. 3)
- Wednesday, December 9
Deep Learning and NLP (continued)
Part VI: Philosophy and AI
- Tuesday, December 15
Topic: Philosophy and AI
Suggested Reading: R&N Chapter 26
and "Computing
Machinery and Intelligence" (Turing, 1950)
- Wednesday, December 16
Philosophy and AI (continued)
