News: As of January 2009, I have moved to the University of Michigan, where I am a Professor of Computer Science and Engineering in the EECS Department.

The right music at the right time: adaptive personalized playlists based on sequence modeling. Elad Liebman, Maytal Saar-Tsechansky, and Peter Stone Peter Stone. Management Information Systems ...

Since a number of years I am familiar with the observation that the quality of programmers is a decreasing function of the density of go to statements in the programs they produce. Later I discovered ...

One vision of a future artificial intelligence (AI) is where many separate unitscan learn independently over a lifetime and share their knowledge with eachother. The synergy between lifelong learning ...

Rectified Flow # As distributions are the central object in statistics and machine learning, many fundamental learning problems, such as generative modeling and domain transfer, can be unifiedly ...

Coding in the Classroom is an outreach initiative in which members of the UT Computer Science community teach coding in local schools, introducing computer science to a broad group of students and ...

Now in its second year, the Dijkstra Scholars Program is a transformational initiative designed to dismantle barriers to a ...

My main research interest is in computational theories of the brain with emphasis on human vision and motor control. In 1985 Chris Brown and I led a team that designed and built a high speed binocular ...

Recent advances of locomotion controllers utilizing deep reinforcement learning(RL) have yielded impressive results in terms of achieving rapid and robustlocomotion across challenging terrain, such as ...

Jump to section: This is the official site of the UT Austin Villa 3D Simulation team from the Department of Computer Science at the University of Texas at Austin. In the RoboCup 3D Simulation League ...

1 On our inability to do much. 4 On the reliability of mechanisms. 8 On our mental aids. 15 An example of a correctness proof. 19 On the validity of proofs versus the validity of implementations. 21 ...

The state space is far too large to explore exhaustively; Each agent has only partial state information; The action space is continuous; Multiple teammates need to learn simultaneously. Despite these ...