CMPUT366 Schedule, Slides, Readings (tentative)

The numbers in [] brackets are the relevant chapters of the [Russell/Norvig] textbook;
those in () parentheses are from the (Poole/Mackworth/Goebel) textbook, and are OPTIONAL reading.

L#1 Administrivia
AI = the design of rational agents
[1.1, 1.4],    (1)  AI in the News
AI (the movie)
What is AI?
L#2a Structure of intelligent agents and environments [2]
(Environment is observable, deterministic, static, discrete; 
  ... known and modeled using arbitrary code)
L#2b Problems and problem spaces
"Blind Search"
[3.1, 3.2, 3.3],      (4)
[3.4 - 3.6]
L#3 "Informed Search" [4.1, 4.2]
AIxploratorium A* (Wikipedia)
L#4 Constraint satisfaction search (CSP) [3.7],              (4.7) 
Wikipedia on Constraint Satisfaction
On-Line Guide to CP
CP Conference
URL (EPFL)   URL (Temple)
Tutorial on CP
L#5 "Local Search", Stochastic Algorithms [4.3 - 4.4, 7.6]
Selman's page
Boolean Satisfiability (URL)
L#7 Game playing search  (J. Schaeffer)
(RG notes) (DL notes) (S Russell notes)
Games Group (UofA)
LA Times article
L#6b Summary of search [4.6, 5.5,6.8]
  (Environment is inaccessible, deterministic, *, discrete; 
  ... known and modeled using logical inference)
Reasoning, Logic, Wumpus world
Propositional Logic (Semantics, Logical Entailment, Proof Process (Resolution))
[7],         (2 - 2.5)
L#9 Predicate Calculus Representation (Syntax, Semantics, Expressiveness) [8]      (3)
L#10 Predicate Calculus Inference (Resolution) [9]      (5)
L#11 Implemented Systems (Tradeoffs) [10]  
OnLine Prolog Resources
Recent Survey Article
[Omitted] Situation Calculus
"Graph Plan"
L#12 Planning (Simple) [11]                       (8)
Recent Survey Article
L#12b Summary of Logical Agents  
  (Environment is (in)accessible, nondeterministic; 
 .... known and modeled using belief networks)
L#13 Introduction to Decision Theory, Probability (Belief Nets) [13], [14.1]     (10.1 - 10.3)
Bayes Rule Applet
L#14 Belief Net Intro [14 - 14.3]
See also Cmput652 (Probabilistic Graphical Models) Slides
RoadMap (dated!)
(Koller  slides)
Relevant URL Book: Bayesian Networks and Decision Graphs
L#15 Belief Net Inference [14.4-14.8]
(Bucket Elimination paper [Dechter])
(Details of Bucket Elimination)
(Auxiliary notes on Bucket Elimination)
L#16 Dynamic Belief Nets [15]
Chapter (K Murphy)
L#17 Simple Decisions (Utility-based Agents, Influence diagrams, Value of Information) [16],    (10.4) 
L#18-19 Complex (Sequential) Decisions
MDP, Value Iteration, Policy iteration, TD(λ) (dynamic programming)
[17.1- 17.3], [21.2]
Decision Theoretic Planning...[Boutilier'99]
L#19b POMDP, Dynamic decision networks [17.4 - 17.6]
L#20 Game Theory & Mechanism Design [17.6-17.7]
Book: Thinking Strategically
[Omitted] Applying Game Theory to Poker, Network Traffic and Combinatorial Auctions
(R Holte)
Approximating Game-Theoretic Optimal Strategies for Full-scale Poker
Combinatorial Auctions, Knapsack Problems, and Hill-climbing search
Network Routing
  (Communicating Agents))
L#21 Intro to Natural Language
(G Kondrak)
22 (esp. 22.2 - 22.3)
Chart Parser (Eisner)
  (Environment is accessible, ... unknown)
Intro to Machine Learning
Decision Tree Foundations, Entropy
[18.1-18.4],   (11)
See also Cmput466 Material
L#24 Computational Learning Theory [18.5]

I gratefully acknowledge the assistance of Thomas Dietterich, Robert Holte, Daphne Koller, Dekang Lin, Andrew Moore, David Poole, Stuart Russell, Bart Selman and Jia You for allowing me to use some of their material as part of my lecture notes, assignments, etc.

Russ Greiner ,