Courses

On Campus Courses

Notes for students

Online Courses

Introduction to Machine Learning (The Great Courses)

Introduction to Machine LearningTaught by Professor Michael L. Littman of Brown University, this course teaches you about machine-learning programs and how to write them in the Python programming language. For those new to Python, a “get-started” tutorial is included. The professor covers major concepts and techniques, all illustrated with real-world examples such as medical diagnosis, game-playing, spam filters, and media special effects.

Markov Decision Processes, guest lecture on the reward hypothesis, (Coursera)

Michael Littman: The Reward Hypothesis - Markov Decision Processes | CourseraVideo created by University of Alberta, Alberta Machine Intelligence Institute for the course "Fundamentals of Reinforcement Learning". When you’re presented with a problem in industry, the first and most important step is to translate that ...

Machine Learning, with Charles Isbell (GT/Udacity)

Machine Learning | UdacityIn this course, you'll learn how to apply Supervised, Unsupervised and Reinforcement Learning techniques for solving a range of data science problems.

Reinforcement Learning, with Charles Isbell (GT/Udacity)

Reinforcement Learning | UdacityStudy machine learning at a deeper level and become a participant in the reinforcement learning research community.

Intro to Algorithms (Udacity)

Intro to Algorithms | UdacityThis class will give you an introduction to the design and analysis of algorithms, enabling you to analyze networks and discover how individuals are connected.

On Campus Courses

Fall 2021, Learning and Sequential Decision Making.

Summer 2021, Introduction to Discrete Structures & Probability

Fall 2019, Learning and Sequential Decision Making.

Fall 2018, CS15 (staff).

Spring 2020, Introduction to Discrete Structures & Probability

Spring 2018, Machine learning (ML parody videos).

Fall 2017, Learning and Sequential Decision Making.

Fall 2017, CS15 (staff).

Spring 2017, A First Byte of Computer Science.

Fall 2015, Learning and Sequential Decision Making.

Fall 2015, Designing Humanity Centered Robots (with Ian Gonsher).

Spring 2015, A First Byte of Computer Science.

Fall 2014, Designing Humanity Centered Robots (with Ian Gonsher).

Spring 2014, A First Byte of Computer Science.

Fall 2013, Learning and Sequential Decision Making.

Spring 2013, Introduction to Artificial Intelligence.

Fall 2012, Learning and Sequential Decision Making.

Spring 2010, Programming for the Masses (Rutgers).

Spring 2009, Sequential decision making (Rutgers).

Fall 2008, Great Insights in Computer Science (Rutgers).

Fall 2008, Bayesian Reinforcement Learning (Rutgers).

Fall 2007, Great Insights in Computer Science (Rutgers).

Fall 2007, Planning in Learned Environments (Rutgers).

Spring 2007, Great Insights in Computer Science (Rutgers).

Spring 2007, Multiagent reinforcement learning (Rutgers).

Fall 2006, Great Insights in Computer Science (Rutgers).

Fall 2006, Light seminar on reinforcement-learning theory (Rutgers).

Spring 2006, Great Insights in Computer Science (Rutgers).

Fall 2005, Learning and Sequential Decision Making (Rutgers).

Spring 2005, Discrete Math (Rutgers).

Spring 2005, Social Reinforcement Learning (Rutgers, with Matthew Stone).

Fall 2004, Discrete Math (Rutgers).

Fall 2004, Machine Learning (Rutgers).

Spring 2004, Learning and Sequential Decision Making (Rutgers).

Fall 2003, Machine Learning (Rutgers).

Fall 2003, Learned Representations in AI (Rutgers).

Spring 2003, Learning Robots Reading Group (Rutgers).

Fall 2001, Introduction to Artificial Intelligence (Princeton).

Students

Here is a list of the PhD dissertations (theses) I have advised.

My Rutgers students were members of The Rutgers Laboratory for Real-Life Reinforcement Learning (or RL³).

Notes for students

Due to my new position at the NSF, I am not accepting PhD students at this time.
Please check my requests before asking for recommendation letters.
There are editorial comments I make very frequently.
I prefer some names more than others.

Personal links

Archive of recordings of the Littman Family Quartet.
My Dancing with the Profs pre-dance video and performance (2015).
Old links to the "upod" site on end-user programmable devices.
I ran on all the Streets of Barrington to get to know my new town (2013).
Blogger for The Huffington Post, with Lisa Littman (2011).
"Who Are You?" Puzzle at the American Crossword Puzzle Tournament (2010)
With my CS205 class, we had thought we found a bug in the US Constitution (2005).
I have written Humanistic Judaism songs with lyrics sung to the tune of existing songs.
My family and his family sang Justin Boyan a song for his 40th birthday. Similarly, I put up a file with some of my favorite quotes from Charles Isbell when he turned 40.
My explanation of the Monty Hall Problem (Jan. 2006).
I compiled a list of Communication Technology Firsts.
I've started keeping track of slogans that help me understand the world around me.

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