CSE 471/598 Lecture Notes (Fall 2006)

Next offering (by Rao): Fall 2007

Here is what students said about Fall 2006 offering

• Week 1: Intro; Intelligent agent design [[nifty 2001 ]]
  • Audio of [Aug 22, 2006]
  • Audio of [Aug 24, 2006]

• Week 2: Problem Solving Agents and Search (start of A*)
  • Audio of [Aug 29, 2006]
  • Audio of [Aug 31, 2006]

• Week 3: Search: Blind;uniform cost search; A* start
  • Audio of [Sept 5, 2006] (A*, Heuristics)
  • Audio of [Sept 7, 2006] (SMA*,Local search)

• Week 4: Complete local search; start planning
  • Audio of [Sept 12, 2006] (Min-conflict search; genetic search; systematic vs. local search; planning )
  • Audio of [Sept 14, 2006] Planning vs. Search; Progression, Regression, Plan-space planning

• Week 5: Planning Graph Reachability Heuristics; MDP start
  • Audio of [Sep 19, 2006] (Planning Graphs; Mutual Exclusions; Relaxed plans).
  • Audio of [Sep 21, 2006] (Graphplan; Mutexes; PGs for progression vs regression vs partial order planning; MDP start)

• Week 6: MDPs continued; Adversarial Search
  • Audio of [Sep 26, 2006] Markov Decision Processes (Value iteration, policy iteration, RTDP)
  • Audio of [Sep 28, 2006]: Game Tree Search.

• Week 7: Start of Logical Inference
  • Audio of[Oct 3, 2006] (Quiescence, secondary search, alpha-beta best-case; Knowlege representation, entailment, proof vs. model theoretic entailment).
  • Audio of [Oct 5, 2006] (Spectrum of logics, propositional satisfiability and theorem proving)

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• Week 8: Probabilistic Propositional Logic
  • Audio of[Oct 10, 2006] (From propositional logic to probabilistics propositional logic: Complications with Complications; Potatoes in the tailpipes; Magical Ostritches; patients with flu wanting to know if they have a runny nose; ).
  • Audio of[Oct 12, 2006] (distributions, probability vs. statistics as inference with the model vs. learning the model; elemenatary discrete variable probability theory; Bayes rule and Bayesian inference; conditional independence)

• Week 9: Bayes Networks. Semantics and Specification
  • Audio of[Oct 17, 2006] (Conditional Independence Assertions; Bayes Nets; Bayes Ball)
  • Audio of[Oct 19, 2006] (More on conditional indep; specifying bayes networks; parameterized CPTs; introducing hidden variables etc )

• Week 10: Bayes Networks. Inference--Exact and Approximate
  • Audio of[Oct 24, 2006] (Inference with Bayes Nets; Variable elimination; irrelevant variables; sampling based inference methods)

• Week 11: First Order Logic
  • Audio of [Oct 31, 2006] (First order logic: Syntax, Writing knowledge bases)
  • Audio of [Nov 2, 2006] (First order logic; Semantics; Herbrand bases etc; Generalized modus ponens, unification)

• Week 12: FOPC--Backward Chaining; Resolution; Start of Reasoning with Time and Change
  • Audio of [Nov 7, 2006] (Backward Chaining vs. Forward chaining; deductive databases, Existential Proofs; Skolemization/Clausal Forms; Resolution Theorem Proving)
  • Audio of [Nov 9, 2006] (Situation Calculus; Temporal Probabilistic Models; Some informal discussion after the class got recorded. Ignore after 1hr15min)

• Week 13: Reasoning with Time and Change (contd.); Learning (start)
  • Audio of [Nov 11, 2006] (Dynamic Bayes Nets; Inference Problems; Inference Techniques (including Particle Filters); Special Cases: Hidden Markov Models; Markov Chains; Kalman Filters)

  Week 13: Learning (start)

  • Audio of [Nov 16, 2006] Learning; Dimensions of learning problems, Classification/pure-inductive learning; Testing performance of learners; PAC learning (start)

• Week 14: Splendors of Bias; Decision Trees; Naive Bayes classifiers; Neural nets
  • Audio of [Nov 21, 2006] BIASES and their effect on learning (strong vs. weak biases; domain-specific vs. domain independent ones; effect of biases on learning cost and accuracy; Decision Tree learning
  • Audio of [Nov 22, 2006] Decision Tree learning; Neural Networks and Perceptron learning; Introduction to Max-Margin learning
    • ( Here is the Video! (warning: 718mb))

• Week 15:Support Vector M/c; Kernelization; Statistical Learning; Naive Bayes Classifiers
  • Audio of [Nov 30, 2006]

• Week 16: Swan Song
  • Audio of [Dec 5, 2006]: Conclusion of Statistical Learning; Interactive review (see the link below for better recording of student comments), parting comments
    • Audio Recording of student's comments (see above link for Rao's rejoinders)

Wish list:
Reasoning with change: Situation Calculus; Dynamic Bayes nets (Granted!)
Learning: Reinforcement Learning in addition to.. (Naive bayes; decision trees; version spaces; Reinforcement Learning)
CSP and SAT