Steam-powered Turing Machine University of Washington Department of Computer Science & Engineering
CSE P573 - Applications of Artificial Intelligence - Autumn2012
Monday 6:30-9:20 pm in MGH 231
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Instructor: Mausam
(mausam at cs dot washington dot edu)
Office hours: by appointment, CSE 454
TA: Dvijotham Krishnamurthy
(dvij at cs dot washington dot edu)
Office hours: Monday 5:30-6:30, CSE 218

Schedule

Week Dates Topics & Lecture Notes Readings Additional Resources Calendar
1 Sep 24 Introduction, Uninformed Search AIMA Chapters 1,3.1-3.4.3
Applications of AI
Intuition of Search Algorithms
Search Algorithms Performance

2 Oct 1 Uninformed Search (contd) (Video)
Informed Search (Video)
Local Search (Video)
AIMA 3.4.4-3.7,4.1-4.2
Beam Search
IDA*
A*/IDA* Example
Pattern Databases
Stochastic Beam Search
Evolving Monalisa through Genetic Algorithms
Evolving TSP with Genetic Algorithms
Mixability for Genetic Algorithms (pages 66-68)
Prog. A1 released 10/1
Written A1 released 10/2
Written A1 due 10/7
3 Oct 8 Constraint Satisfaction (Video)
AIMA 6
Conversion to Binary CSP
NumberJack
Constraint Programming
Written A2 released 10/9
Written A2 due 10/14
Prog. A1 due noon 10/15
4 Oct 15 Logic and Satisfiability (Video)
Advanced Satisfiability (Video)
AIMA 7, 8.1-8.3
Advanced SAT Solvers (Sections 2.3, 2.4)
AIMA 9
CSP vs. SAT
Phase Transitions
Backdoors
Prog. A2 released 10/15
Written A3 released 10/16
Written A3 due 10/21
5 Oct 22 Adversarial Search, Classical Planning AIMA 5, 10
How Intelligent is Deep Blue?
FF Planner
Written A4 released 10/23
Written A4 due 10/29 6 pm
6 Oct 29 Decision Theory (Video)
Markov Decision Processes (Video)
AIMA 16.1-16.3, 16.6, 17.1-17.4
Planning with MDPs
Prog. A2 due 11/4 noon
Prog. A3 released 11/2
No written assignment
7 Nov 5 Intro to Probability (Video)
Bayesian Networks (Video)
AIMA 13, 14.1-14.4
History of Bayes Theorem
Influence Flow in Bayes Nets
Graphical Models
Written A5 released 11/6
8 Nov 12 Veteran's day. No class


Written A5 due 11/14
Prog. A3 due 11/19 noon
9 Nov 19 Bayes Net Exact Inference (Video)
Bayes Net Approximate Inference (Video)
Bayes Net Learning (Video)
AIMA 14.5, 20
Log Probabilities
Prog. A4 released 11/19
10 Nov 26 Reinforcement Learning (Video1, Video2)
Intro to NLP
AIMA 21.1-21.3, 22.3, 22.4.6
Monte Carlo Planning (Sections 3.1-3.3)
Monte Carlo Planning
Future of Web Search,
IBM Watson Deep QA
Written A6 released 11/27
Written A6 due 12/2
Prog. A4 due 12/3 noon
11 Dec 3 Research Talk: Decision-theoretic Crowdsourcing
Agents and WrapUp (Video)
EndCourse Discussion
AIMA 2, 27
AI for Crowdsourcing
Dawn of AI

12 Dec 10 Final Exam
Whole Course



Textbook

Stuart Russell & Peter Norvig, Artificial Intelligence: A Modern Approach,
Prentice-Hall, Third Edition (2009) (required).

Grading

Programming Assignments: 50%; Written Assignments: 20%; Final: 30%.

There will be four programming assignments due approximately every two weeks. There will be nine small written assignments due approximately every week.

The gradebook can be found here.

Course Administration and Policies

Cheating Vs. Collaborating Guidelines

As referenced from Dan Weld's guidelines.

Collaboration is a very good thing. On the other hand, cheating is considered a very serious offense. Please don't do it! Concern about cheating creates an unpleasant environment for everyone. If you cheat, you risk losing your position as a student in the department and the college. The department's policy on cheating is to report any cases to the college cheating committee. What follows afterwards is not fun.

So how do you draw the line between collaboration and cheating? Here's a reasonable set of ground rules. Failure to understand and follow these rules will constitute cheating, and will be dealt with as per University guidelines.


CSE logo Department of Computer Science & Engineering
University of Washington
Box 352350
Seattle, WA  98195-2350
(206) 543-1695 voice, (206) 543-2969 FAX