Monday September 10 Lecture 1 Intro to AI and CS 486/686
Slides in PDF
Wednesday September 12 Lecture 2 Search: Problem Formulation
Slides in PDF
Notes in PDF (Updated Mon Sept 17)
Scanned Notes in PDF
Monday September 17 Lecture 3 Uninformed Search
Slides in PDF
Scanned Notes in PDF (Posted Tue Sept 18)
Figure 3.19 on Iterative Deepening Search from Textbook (Posted Tue Sept 18)
Wednesday September 19 Lecture 4 Informed Search
Slides on Informed Search
Notes on Informed Search (Updated Wed Sept 26)
Monday September 24 Lecture 5 Introduction to CSPs
Slides on CSP (Updated Tue Sept 25)
Notes on CSP formulations (Uploaded Tue Oct 2)
Wednesday September 26 Lecture 6 Backtracking Search
Slides in PDF
Notes on Arc Consistency and Backtracking Search (Uploaded Wed Sept 26)
Examples of Forward Checking and Maintaining Arc Consistency (Uploaded Sun Oct 7)
Monday October 1 Lecture 7 Local Search
Slides on Local Search
Notes on Uninformed Search and Backtracking Search (Uploaded Mon Oct 1)
Wednesday October 3 Lecture 8 Local Search
Slides on Local Search
Notes on Hill Climbing, Simulated Annealing and Genetic Algorithms (Uploaded Wed Oct 3)
Friday October 12 Lecture 9 Probabilities
Slides on Probabilities
Notes on Probabilities (Updated Tue Oct 16)
Monday October 15 Lecture 10 Independence and Intro to Bayes Nets
Slides on Independence
Slides on Intro to Bayes Nets
Review of Probabilities (Updated Tue Oct 16)
Clarifying Notation (Uploaded Tue Oct 16)
Bayesian Network for the Holmes Scenario
Wednesday October 17 Lecture 11 Constructing Bayesian Networks
Slides on Constructing Bayesian Networks
Bayesian Network for the Holmes Scenario
Semantics of a Bayesian Network (Uploaded Tue Oct 23)
Construct a Bayesian Network (Uploaded Thu Oct 18)
Monday October 22 Lecture 12 Inference in Bayesian Networks
Slides on Variable Elimination Algorithm
Inference in the Holmes Bayesian Network (Updated Fri Nov 2)
The variable elimination algorithm (Updated Fri Nov 2)
Wednesday October 24 Lecture 13 Intro to Decision Networks
Slides on Decision Networks
Robot Decision Network Handout
The mail delivery robot example
Monday October 29 Lecture 14 Define a Markov Decision Process
Slides with clicker questions
Define a Markov Decision Process
Wednesday October 31 Lecture 15 The value iteration algorithm to solve a MDP
Slides with clicker questions
The value iteration algorithm
Monday November 5 Lecture 16 Game Theory
Slides on game theory
2-player normal form games (part 1) (Updated Wed Nov 7)
Wednesday November 7 Lecture 17 Game Theory
Slides on game theory
2-player normal form games (parts 1 and 2) (Updated Thu Nov 8)
Monday November 12 Lecture 18 Intro to Learning and Decision Trees
Slides on intro to learning
Slides on intro to decision trees
Notes on intro to learning and decision trees (Uploaded Tue Nov 13)
Notes on intro to learning (Uploaded Tue Nov 13)
Notes on intro to decision trees (Uploaded Tue Nov 13)
Wednesday November 14 Lecture 19 Intro to Decision Trees
Slides on constructing decision trees
Notes on decision trees
Monday November 19 Lecture 20 Extending Decision Trees
Slides on extending decision trees
Notes on extending decision trees (Uploaded Fri Nov 23 with more details on choosing split points)
Wednesday November 21 Lecture 21 A brief history of deep learning
Notes on a brief history of deep learning
Monday November 26 Lecture 22 Representing XOR and the backpropagation algorithm
See the notes for lecture 23 below.
Wednesday November 28 Lecture 23 Representing XOR and the backpropagation algorithm
Notes on neural networks