Prerequisites: Graduate standing or consent of instructor. Many students find this course difficult, so a first-rate math background is highly recommended. See the Review Sheet for material you're ...

E. Allen Emerson, a beloved and long-serving member of the faculty in Computer Science at UT Austin and a renowned Computer ...

Artificial Intelligence and Life in 2030. Peter Stone, Rodney Brooks, Erik Brynjolfsson, Ryan Calo, Oren Etzioni, Greg Hager, Julia Hirschberg, Shivaram ...

In reinforcement learning (RL), a reward function that aligns exactly with a task's true performance metric is often sparse. For example, a true task metric might encode a reward of 1 upon success and ...

Policy Gradient Reinforcement Learning for Fast Quadrupedal Locomotion. Nate Kohl and Peter Stone.

The goal of this study is to explore which aspects of people’s analytical decision making are affected when ex- posed to music. To this end, we apply a stochastic sequen- tial model of simple ...

Multiagent Systems: A survey from a machine learning perspective. Peter Stone and Manuela Veloso. Autonomous Robots, 8(3):345–383, July 2000. @Article(MASsurvey, Author="Peter Stone and Manuela Veloso ...

Exploiting full-body dynamics in feedback control can enhance the balancing capability of a legged system using various techniques such as Whole-Body Control (WBC) or Centroidal Momentum control.

Classically, imitation learning algorithms have been developed for idealized situations, e.g., the demonstrations are often required to be collected in the exact same environment and usually include ...

David Pardoe and Peter Stone.

Recent work has shown that deep neural networks are capable ofapproximating both value functions and policies in reinforcementlearning domains featuring continuous state and actionspaces. However, to ...