Recent advances in autonomous vehicle technology will open the door to highlyefficient transportation systems in the future, as demonstrated by Autonomous Intersection Management, an intersection ...

Adding Influencing Agents to a Flock. Katie Genter and Peter Stone. @InProceedings{AAMAS16-katie, author = {Katie Genter and Peter Stone}, title = {Adding Influencing Agents to a Flock}, booktitle = ...

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 ...

Bilevel optimization (BO) is useful for solving a variety of important machine learning problems including but not limited to hyperparameter optimization, meta-learning, continual learning, and ...

Course Overview: Spectral graph theory studies how algebraic properties of matrices, most notably eigenvalues and eigenvectors, give information about the combinatorial structure of graphs, such as ...

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 ...

Our students and faculty are changing the world through their contributions to computing education, research, and industry. These awards received by members of the UT Computer Science community make ...

Gaussian processes for sample efficient reinforcement learning with RMAX-like exploration. Tobias Jung and Peter Stone. @InProceedings{ECML10-jung, author = "Tobias Jung and Peter Stone", title = ...