Instructor:  Prof. Henry Kautz  Office Hours: Friday 12:00 noon  1:00pm, CSB 709 
Grad TA:  Xiaowan Dong  Office Hours: 5:006:00pm Tuesday & Wednesday, CSB 724 
Undergrad TAs:  Sean Esterkin 
Office Hours: 5:006:00pm Monday, 12:301:30pm Thursday, CSB 633 (CS Majors Lab) 
Classroom  Meliora 203 
Dishonesty: Claiming work by others as your own without attribution, unauthorized collaboration with other students. All cases will be referred to Academic Honesty Board.
Accommodations: I will make appropriate accommodations for students with learning differences. Inform me in writing within the first two weeks of class. Make an appointment to talk with me about differences that require accommodations beyond extra time on tests.
Coursework:
Programming: Projects must run on Linux on URCS instructional network. If you do not have an account (nonmajors), contact grad TA Xiaowan Dong. Can use any language: Java, C, Python, LISP, Prolog, etc.
Project 2 Planning as Satisfiabillity
date  lecture slides  assignments 
21 Jan  Lecture 01  Introduction  
23 Jan  Lecture 02  Problem Solving  Homework: Read Chapters 2 and 3 this weekend 
28 Jan  Lecture 03  Search Strategies  
30 Jan  Lecture 04  Local Search  Search Algorithm Demos. Demos are Java applets. If you are running Java 7 version 51 or newer, you must add this domain http://www.cs.rochester.edu to Exception Site List (whitelist) in Java preferences in Settings or Control Panel.
Homework 01 Search posted. Solutions will be handed out in class on Thursday 6 February. You will need to know how to problems similar to these on the exams! Also, read Chapter 4 of AIMA. 
4 Feb  Lecture 05  Adversarial Search  
6 Feb  Lecture 06  AlphaBeta Pruning  Project 1 Othello posted 
11 Feb  Homework 02 Games posted  
13 Feb  Lecture 08 Propositional Logic  
18 Feb  Lecture 09 Propositional Inference  Homework 02 solutions given out in class 
20 Feb  Exam 1: Search  
25 Feb  Lecture 10 FirstOrder Logic  
27 Feb  Lecture 11 FirstOrder Inference  Othello Phase I due 
4 Mar  Planning I  ULW Outlines due (hardcopy) 
6 Mar  Planning II  Homework 03 solutions given out in class 
March Break  
18 Mar  Exam 2: Logic  
20 Mar  Probabilistic Reasoning  Othello Phase II and Othello Phase III (Optional) due 
25 Mar  Bayesian Networks  
27 Mar  Learning & Approximate Inference in Bayesian Networks  
1 Apr  (Class cancelled)  ULW First Draft due (hardcopy) 
3 Apr  Learning from Examples  Homework 04 solutions are in the box outside of CSB 709 
8 Apr  Exam 3: Probability & Learning I  Project 2 due 
10 Apr  Project 3 Neural Networks posted Reading on Blackboard Reserves: Chapter 4: Artificial Neural Networks, in T. Mitchell, Machine Learning, McGrawHill, 1997. 

15 Apr  
17 Apr  Workshop  
22 Apr  Reinforcement Learning  
24 Apr 
(Same slides as previous lecture) 
Homework 05 Learning and All Course Review posted. Solutions with not be given out for this assignment. You should complete all the problems in order to prepare yourself for the final exam. 
29 Apr  Wrap Up and Review  Project 3 due ULW Final Draft due (hardcopy) 
9 May  4:006:00pm Final Exam  Learning II + all previous material 