MIL - The University of Tennessee
the university of tennessee machine intelligence lab
  
Scott Livingston, Ph.D. student at CalTech
[ cv
  
Science and Engineering Facility Room 204
1414 Circle Drive
University of Tennessee
Knoxville, TN 37996-2100


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Research Reinforcement Learning and Approximate Dynamic Programming 
  
  Reinforcement Learning and Approximate Dynamic Programming
  I studied the behavior of recurrent neural networks acting as function approximators in the context of reinforcement learning. I am more generally interested in machine learning and control, especially in robotics.
  
Selected Publications
  
[1]     I. Arel, S. Livingston, "Beyond the Turing Test," IEEE Computer, Vol. 42, No. 3, pp. 104-105, March, 2009 [pdf]
[2]     I. Elhanany, C. Niedzwiedz, Z. Liu, S. Livingston, "A Consolidated Actor-Critic Model for Partially-Observable Markov Decision Processes," IET Electronics Letters, October, 2008 [pdf]
[3]     C. Niedzwiedz, I. Elhanany, Z. Liu, S. Livingston, "A Consolidated Actor-Critic Model with Function Approximation for High-Dimensional POMDPs," AAAI 2008 workshop for Advancement in POMDP Solvers (part of the AAAI 2008 Conference), Chicago, July, 2008 [pdf]
[4]     C. Niedzwiedz, Z. Liu, I. Elhanany, S. Livingston, "A Consolidated Actor-Critic Model for Temporal Difference Learning with Function Approximation and Application to POMDPs," 3rd Northeast Student Colloquium on Artificial Intelligence, May, 2008 [pdf]
[5]     S. Livingston, J. Garvey, I. Elhanany, "On the Broad Implications of Reinforcement Learning based Artificial General Intelligence (AGI)," AGI-08 Workshop on the Sociocultural, Ethical and Futurological Implications of Artificial General Intelligence, March, 2008 [pdf]