Course web page: http://www.cs.utexas.edu/~ecprice/courses/randomized/fa23/ ...

Patrick MacAlpine and Peter Stone.

Though computers have surpassed humans at many tasks, especially computationally intensive ones, there are many tasks for which human expertise remains necessary and/or useful. For such tasks, it is ...

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

RoboCup-2012: Robot Soccer World Cup XVI, Xiaoping Chen, Peter Stone, Luis Enrique Sucar, and Tijn van der Zant, editors. Lecture Notes in Artificial Intelligence, Springer Verlag, Berlin, 2013.

TEXPLORE: Real-Time Sample-Efficient Reinforcement Learning for Robots. Todd Hester and Peter Stone. Machine Learning, 90(3):385–429, 2013.

Soccer is a rich domain for the study of multiagent learning issues. Not only must the players learn low-level skills, but they must also learn to work together and to adapt to the behaviors of ...

Scalable Multiagent Driving Policies For Reducing Traffic Congestion. Jiaxun Cui, William Macke, Harel Yedidsion, Aastha Goyal, Daniel Urieli, and Peter Stone. In Proceedings of the 20th International ...

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 ...

Mobile Robot Planning using Action Language BC with an Abstraction Hierarchy. Shiqi Zhang, Fangkai Yang, Piyush Khandelwal, and Peter Stone. In Proceedings of the 13th International Conference on ...

Multi-robot planning (mrp) aims at computing plans, each in the form of a sequence of actions, for a team of robots to achieve their individual goals, while minimizing overall cost. Solving mrp ...

We provide a unified framework for the high-dimensional analysis of “superposition-structured” or “dirty” statistical models: where the model parameters are a “superposition” of structurally ...