Adam White

Postdoctoral researcher
Department of Computer Science
School of Informatics and Computing
Indiana University
















adamw@indiana.edu
(812) 292-0149
I graduated from the University of Alberta with a Ph.D. in Computing Science in 2015. During my doctoral studies I was advised by Richard Sutton, working in the RLAI lab.


Teaching

CSCI-B 659: Reinforcement learning for Artificial Intelligence - Spring 2016

Research

Keywords: Reinforcement Learning, Robotics, Knowledge Representation and Intrinsic Motivation

My research focuses on the problem of Artifical Intelligence, specifically how to replicate or simulate human level intelligence in real and simulated agents. My research program explores how the problem of intelligence can be modelled as a reinforcement learning agent interacting with some unknown enviroment, learning from a scalar reward signal rather than explicit feedback. My contributions include new algorithms for reinforcement learning, and large-scale demonstrations of learning on mobile robots.





Curriculum vitae

My current CV can be found here.

Journal Papers

Modayil, J., White, A., Sutton, R. S. (2014). Multi-timescale Nexting in a Reinforcement Learning Robot. Adaptive Behavior, 22(2):146--160.

Whiteson, S., Tanner, B., & White, A. (2010). The reinforcement learning competitions. AI Magazine, 31(2): 81--94.

Tanner, B., & White, A. (2009). RL-Glue: Language-independent software for reinforcement-learning experiments. The Journal of Machine Learning Research, 10: 2133--2136.


Conference Papers

Sherstan, C., Machado, M., ,White, A., Patrick P. (2016). Introspective Agents: Confidence Measures for General Value Functions, Artificial General Intelligence (AGI).

White, A., White M. (2016). Investigating practical linear temporal difference learning. In International Conference on Autonomous Agents and MultiAgent Systems (AAMAS). [ CODE ]

White, M., White A. (2016) Adapting the trace parameter in reinforcement learning, In International Conference on Autonomous Agents and MultiAgent Systems (AAMAS).

White, A., Modayil, J., & Sutton, R. S. (2012). Scaling life-long off-policy learning. In the IEEE International Conference on Development and Learning and Epigenetic Robotics, 1--6. [paper of distinction award]

Modayil, J., White, A., Pilarski, P. M., & Sutton, R. S. (2012). Acquiring a broad range of empirical knowledge in real time by temporal-difference learning. In the IEEE International Conference on Systems, Man, and Cybernetics, 1903--1910.

Modayil, J., White, A., Sutton, R. S. (2012). Multi-timescale Nexting in a Reinforcement Learning Robot. Presented at the 2012 International Conference on Adaptive Behaviour, Odense, Denmark. To appear in: SAB 12, LNAI 7426, pp. 299-309, T. Ziemke, C. Balkenius, and J. Hallam, Eds., Springer Heidelberg.

Sutton, R. S., Modayil, J., Delp, M., Degris, T., Pilarski, P. M., White, A., & Precup, D. (2011). Horde: A scalable real-time architecture for learning knowledge from unsupervised sensorimotor interaction. In The 10th International Conference on Autonomous Agents and Multiagent Systems: 2, 761--768.

White, M., & White, A. (2010). Interval estimation for reinforcement-learning algorithms in continuous-state domains. In Advances in Neural Information Processing Systems, 2433--2441.

Sturtevant, N. R., & White, A. M. (2007). Feature construction for reinforcement learning in hearts. In Computers and Games . Springer Berlin Heidelberg, 122--134


Other published works

White, A., & Sutton, R. S. (2014). GQ (λ) Quick Reference Guide.

White, A., Modayil, J., & Sutton, R. S. (2014). Surprise and curiosity for big data robotics. In Workshops at the Twenty-Eighth AAAI Conference on Artificial Intelligence.

Modayil, J., White, A., Pilarski, P. M., Sutton, R. S. (2012). Acquiring Diverse Predictive Knowledge in Real Time by Temporal-difference Learning. International Workshop on Evolutionary and Reinforcement Learning for Autonomous Robot Systems, Montpellier, France. [Best paper award]

Modayil, J., Pilarski, P., White, A., Degris, T., & Sutton, R. (2010). Off-policy knowledge maintenance for robots. In Proceedings of Robotics Science and Systems Workshop (Towards Closing the Loop: Active Learning for Robotics) : 55.


Theses

White, A. (2015) Developing a predictive approach to knowledge. Doctoral thesis, University of Alberta.

White, A. (2006) A standard system for benchmarking in reinforcement learning. Master's thesis, University of Alberta.


See my google scholar page for a list of my publications that Google knows about.

Contact info

Office: 201I Lindley Hall

Mail:
School of Informatics and Computing
Indiana University
Bloomington, Indiana
USA