UIUC CS 591, Section EA
Advanced Reasoning in AI
Autumn 2004
Tentative Course Syllabus

Approximate Schedule

Session Date Topic/Readings Sample Application
Reading
Assignment
2
Sep 7
Learning partially observable action models   Eyal Amir
3
Sep 14
Aggregating Learned Probabilistic Beliefs (ps)   Pedrito Maynard-Zhang
4
Sep 21
Compiling control knowledge into preconditions for planning in the situation calculus   Phil Oertel
5
Sep 28
Automation of proof by mathematical induction (book chapter from Handbook)   Ken Keefe
6
Oct 5
Efficiently Inducing Features of Conditional Random Fields, Andrew McCallum. UAI 2003   Abhishek Tiwari
7
Oct 12
Linear belief functions   Jeff Pasternack
8
Oct 19
Extending KB approach to Planning with sensing   Hannaneh Hajishirzi
9
Oct 26
Generalized version of resolution   Deepak Ramachandran
10
Nov 2
Logic of motion   Chi Trinh
11
Nov 9
Representing beliefs in fluent calculus   Afsaneh Shirazi
12
Nov 16
Frame problem and Bayesian Networks   Brian Hlubocky
13
Nov 30
Learning in Bayesian Networks / Learning to reason / hardness of approximate reasoning   Steve Lauderberg
14
Dec 7
Case-factor diagrams for structured probabilistic modeling   Tony Bergstron

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Comments to Eyal Amir