Reinforcement Learning and Artificial Intelligence (RLAI)
	CMPUT 499/609 (2004): Reinforcement Learning in Artificial Intelligence

• Course description, basic info on the course
  
• Schedule
• Online version of the textbook
• Python information
• Reinforcement learning interface documentation
• FAQ (please refer to this before sending questions to the TA)
  
• Exercise for Chapter 1 (due September 21): Run and analyze Nim agent (Update Sept 20 to work on Grad Machines)
  
• Exercise and readings for chapter 2 (due Sept 23rd and Sept 28/30th)
• Programming exercise for Chapter 2 - bandit problem (also due Sept 30th)
• Exercises and readings for chapter 3 (due October 4th, 5th, and 7th)
• Exercises and readings for chapter 4 (due October 11th, 12th, and 14th)
• Programming exercise for Chapter 4 - party problem (due October 19th)
  
• Exercises and readings for chapter 5 (due October 18th, 19th, 21th, and 26th)
• Exercises and readings for chapter 6 (due October 26th, 28th, and Nov 2nd)
• Mid Term Exercise (due November 1st)
• Exercises and readings for chapter 7 (due Nov 8th, Nov 9th and Nov 16th)
  
• Exercises and readings for chapter 8 (due Nov 17th, Nov 18th and Nov 23th)
• Refurbished versions of the pseudocode algorithms in Figures 8.8 and 8.9 are here for Sarsa(lambda) with FA and here for Watkins's Q(lambda) with FA.
  
• Function Approximation Assignments (updated and due Thursday Nov 25th)
  
• Exercises and readings for chapter 9 (due Nov 29th, Nov 30th and Dec 2nd)
• Reading and Exercises for chapter 10 (due December 6th and 7th) UPDATED DEC 6
• Literature Review Project for Graduate Students (due Dec 14)
  
• The reinforcement learning hypothesis
• The value function hypothesis
• Graphing software in python
• The RLtoolkit python package
  

Slides

• Chapter 2
• Chapter 3
• Chapter 4
  
• Chapter 5
  
• Chapter 6
  
• Chapter 7
• Chapter 8
  
• Chapter 9

Related Courses Elsewhere

• Peter Stone's course at the University of Texas at Austin
• a student's ideas on exercise 7.3
  
• Yishay Mansour's course at Tel Aviv University
• Nikos Vlassis's course at the University of Amsterdam
• Andy Barto's course at the University of Massachusetts
• USC
• Marco Wiering's course at Utrecht University
• B. Ravindran's course at the Indian Institute of Technology Madras