Department of Computer Science - University of Texas at Austin

Işil Dillig Receives AI for Math Fund Grant to Advance Research in Mathematical Discovery

Through the AI for Math Fund, Renaissance Philanthropy and XTX Markets support projects with the potential to advance ...
Department of Computer Science - University of Texas at Austin

Roberto Martín-Martín Earns 2026 IROS Toshio Fukuda Young Professional Award

The Toshio Fukuda Young Professional Award highlights outstanding individuals within the IROS community who have pioneered activities in robotics and intelligent systems early in their careers. The ...
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CS 378: Symbolic Programming: Online

August 28, 2020: Read-Eval-Print Loop; Quotation September 1, 2020: List Representation rest; if statement lengthfunction Clojure examples September 3, 2020: Recursion Stack Frames, Reverse Append; ...
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Alexander Jones

I'm a freshman at the University of Texas at Austin studying computer science. I've been writing code for almost a decade, and I like building small, fun projects that bring interesting mathematical ...
www.cs.utexas.edu

Outplaying Elite Table Tennis Players with an Autonomous Robot

Outplaying Elite Table Tennis Players with an Autonomous Robot. Peter Duerr, Mireille El Gheche, Guilherme Jorge Maeda, Nobuhiko Mukai, Naoya Takahashi, Stefan Heusser, Hamdi Sahloul, Yamen Saraiji, ...
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SAT 2015

The International Conference on Theory and Applications of Satisfiability Testing (SAT) is the premier annual meeting for researchers focusing on the theory and applications of the propositional ...
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Transfer Learning for Reinforcement Learning Domains: A Survey

Transfer Learning for Reinforcement Learning Domains: A Survey. Matthew E. Taylor and Peter Stone. Journal of Machine Learning Research, 10(1):1633–1685, 2009.
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Boosting for Regression Transfer

David Pardoe and Peter Stone.
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Multiagent Systems: A survey from a machine learning perspective

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 ...
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Deep Recurrent Q-Learning for Partially Observable MDPs

BibTeX Entry @InProceedings {SDMIA15-Hausknecht, author = {Matthew Hausknecht and Peter Stone}, title = {Deep Recurrent Q-Learning for Partially Observable MDPs}, booktitle = {AAAI Fall Symposium on ...
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Deep Reinforcement Learning in Parameterized Action Space

Recent work has shown that deep neural networks are capable of approximating both value functions and policies in reinforcement learning domains featuring continuous state and action spaces. However, ...
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Artificial Intelligence and Life in 2030

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