Daniel Stronger
Ph.D. Alumni
Dan's dissertation presented algorithms enabling an autonomous mobile robot to learn about the effects of its actions and the meanings of its sensations. These action and sensor models are learned without the robot starting with an accurate estimate of either model. These algorithms were implemented and tested on two robotic platforms: a Sony AIBO ERS-7 and an autonomous car. After graduating, Dan joined Morgan Stanley as a trading strategist to model the behavior of illiquid credit derivatives.
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A Neural Network-Based Approach to Robot Motion Control 2008
Uli Grasemann, Daniel Stronger, and Peter Stone, In RoboCup-2007: Robot Soccer World Cup XI, Ubbo Visser and Fernando Ribeiro and Takeshi Ohashi and Frank Dellaert (Eds.), Vol. 5001, pp. 480-87, Berlin 2008. Springer Verlag.
Maximum Likelihood Estimation of Sensor and Action Model Functions on a Mobile Robot 2008
Daniel Stronger and Peter Stone, In IEEE International Conference on Robotics and Automation, May 2008.
Polynomial Regression with Automated Degree: A Function Approximator for Autonomous Agents 2008
Daniel Stronger and Peter Stone, International Journal on Artificial Intelligence Tools, Vol. 17, 1 (2008), pp. 159-174.
A Comparison of Two Approaches for Vision and Self-Localization on a Mobile Robot 2007
Daniel Stronger and Peter Stone, In IEEE International Conference on Robotics and Automation, pp. 3915-3920, April 2007.
Selective Visual Attention for Object Detection on a Legged Robot 2007
Daniel Stronger and Peter Stone, In RoboCup-2006: Robot Soccer World Cup X, Gerhard Lakemeyer and Elizabeth Sklar and Domenico Sorenti and Tomoichi Takahashi (Eds.), Vol. 4434, pp. 158-170, Berlin 2007. Springer Verlag.
From Pixels to Multi-Robot Decision-Making: A Study in Uncertainty 2006
Peter Stone, Mohan Sridharan, Daniel Stronger, Gregory Kuhlmann, Nate Kohl, Peggy Fidelman, and Nicholas K. Jong, Robotics and Autonomous Systems, Vol. 54, 11 (2006), pp. 933-43. Special issue on Planning Under Uncertainty in Robotics..
Towards Autonomous Sensor and Actuator Model Induction on a Mobile Robot 2006
Daniel Stronger and Peter Stone, Connection Science, Vol. 18, 2 (2006), pp. 97-119. Special Issue on Developmental Robotics..
A Model-Based Approach to Robot Joint Control 2005
Daniel Stronger and Peter Stone, In RoboCup-2004: Robot Soccer World Cup VIII, Daniele Nardi and Martin Riedmiller and Claude Sammut (Eds.), Vol. 3276, pp. 297-309, Berlin 2005. Springer Verlag.
The UT Austin Villa 2005 RoboCup Four-Legged Team 2005
Peter Stone, Kurt Dresner, Peggy Fidelman, Nate Kohl, Gregory Kuhlmann, Mohan Sridharan, and Daniel Stronger, Technical Report UT-AI-TR-05-325, The University of Texas at Austin, Department of Computer Sciences, AI Laboratory.
The UT Austin Villa 2003 Four-Legged Team 2004
Peter Stone, Kurt Dresner, Selim T. Erdougan, Peggy Fidelman, Nicholas K. Jong, Nate Kohl, Gregory Kuhlmann, Ellie Lin, Mohan Sridharan, Daniel Stronger, and Gurushyam Hariharan, In RoboCup-2003: Robot Soccer World Cup VII, Daniel Polani and Brett Browning and Andrea Bonarini and Kazuo Yoshida (Eds.), Berlin 2004. Springer Verlag.
The UT Austin Villa 2004 RoboCup Four-Legged Team: Coming of Age 2004
Peter Stone, Kurt Dresner, Peggy Fidelman, Nicholas K. Jong, Nate Kohl, Gregory Kuhlmann, Mohan Sridharan, and Daniel Stronger, Technical Report UT-AI-TR-04-313, The University of Texas at Austin, Department of Computer Sciences, AI Laboratory.
Formerly affiliated with Learning Agents