Daniel Urieli
Ph.D. Alumni
Daniel, an NSF IGERT Graduate Research Fellow, is researching how to design learning agents that solve sustainable energy problems. Such agents need to take robust decisions under uncertainty, while learning, predicting, planning and adapting to changing environments. Daniel's research included designing a learning agent for controlling a smart thermostat, and designing the champion power-trading agent that won the finals of the 2013 Power Trading Agent Competition. Previously, Daniel was part of the champion RoboCup 3D simulation team, UT Austin Villa. Outside work, Daniel enjoys literature, theatre, hiking and biking.
Homepage:
http://www.cs.utexas.edu/~urieli
Publications
     [Expand to show all 14][Minimize]
Learning a Robust Multiagent Driving Policy for Traffic Congestion Reduction 2022
Yulin Zhang, William Macke, Jiaxun Cui, Daniel Urieli, and Peter Stone, In Proceedings of the Adaptive and Learning Agents Workshop (ALA), Auckland, NZ, May 2022.
Scalable Multiagent Driving Policies For Reducing Traffic Congestion 2021
Jiaxun Cui, William Macke, Harel Yedidsion, Aastha Goyal, Daniel Urieli, and Peter Stone, No other information
An MDP-Based Winning Approach to Autonomous Power Trading: Formalization and Empirical Analysis 2016
Daniel Urieli and Peter Stone, In Proceedings of the 15th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2016.
Autonomous Electricity Trading using Time-Of-Use Tariffs in a Competitive Market 2016
Daniel Urieli and Peter Stone, In Proceedings of the 30th Conference on Artificial Intelligence (AAAI 2016), Phoenix, AZ, USA, February 2016.
Autonomous Trading in Modern Electricity Markets 2015
Daniel Urieli, PhD Thesis, Department of Computer Sciences, The University of Texas at Austin. Code and binaries available at: http://www.cs.utexas.edu/~urieli/thesis.
TacTex'13: A Champion Adaptive Power Trading Agent 2014
Daniel Urieli and Peter Stone, In Proceedings of the Twenty-Eighth Conference on Artificial Intelligence (AAAI 2014), July 2014.
A Learning Agent for Heat-Pump Thermostat Control 2013
Daniel Urieli and Peter Stone, In Proceedings of the 12th International Conference on Autonomous Agents and Multiagent Systems (AAMAS'13), May 2013.
Model-Selection for Non-Parametric Function Approximation in Continuous Control Problems: A Case Study in a Smart Energy System 2013
Daniel Urieli and Peter Stone, In Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases (ECML-PKDD'13), September 2013.
Design and Optimization of an Omnidirectional Humanoid Walk: A Winning Approach at the RoboCup 2011 3D Simulation Competition 2012
Patrick MacAlpine, Samuel Barrett, Daniel Urieli, Victor Vu, and Peter Stone, In Twenty-Sixth Conference on Artificial Intelligence (AAAI'12), July 2012.
UT Austin Villa 2011: A Champion Agent in the RoboCup 3D Soccer Simulation Competition 2012
Patrick MacAlpine, Daniel Urieli, Samuel Barrett, Shivaram Kalyanakrishnan, Francisco Barrera, Adrian Lopez-Mobilia, Nicolae Stiurca, Victor Vu, and Peter Stone, In Proc. of 11th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS'12), June 2012.
Wright Eagle and UT Austin Villa: RoboCup 2011 Simulation League Champions 2012
Aijun Bai, Xiaoping Chen, Patrick MacAlpine, Daniel Urieli, Samuel Barrett, and Peter Stone, In {R}obo{C}up-2011: Robot Soccer World Cup {XV} 2012.
Multiagent Patrol Generalized to Complex Environmental Conditions 2011
Noa Agmon, Daniel Urieli, and Peter Stone, In Proceedings of the Twenty-Fifth Conference on Artificial Intelligence (AAAI'11), August 2011.
On Optimizing Interdependent Skills: A Case Study in Simulated 3D Humanoid Robot Soccer 2011
Daniel Urieli, Patrick MacAlpine, Shivaram Kalyanakrishnan, Yinon Bentor, and Peter Stone, In Proc. of 10th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS'11), May 2011.
UT Austin Villa 2011 3D Simulation Team Report 2011
Patrick MacAlpine, Daniel Urieli, Samuel Barrett, Shivaram Kalyanakrishnan, Francisco Barrera, Adrian Lopez-Mobilia, Nicolae Stiurca, Victor Vu, and Peter Stone, Technical Report, Department of Computer Science, The University of Texas at Austin.
Labs
Formerly affiliated with Learning Agents