Publications
The Benefits of Model Based Generalization in Reinforcement Learning
Kenny Young, Aditya Ramesh, Louis Kirsch, Jürgen Schmidhuber
International Conference on Machine Learning (ICML), 2023
Kenny Young
AAAI Conference on Artificial Intelligence (AAAI), 2022
Doubly-Asynchronous Value Iteration: Making Value Iteration Asynchronous in Actions
Tian Tian, Kenny Young, Richard S. Sutton
Conference on Neural Information Processing Systems (NeurIPS), 2022
Kenny Young, Richard S. Sutton
Preprint, 2020
Kenny Young, Baoxiang Wang, Matthew E. Taylor
International Joint Conferences on Artificial Intelligence (IJCAI), 2019
MinAtar: An Atari-Inspired Testbed for Thorough and Reproducible Reinforcement Learning Experiments
Kenny Young, Tian Tian
The Multi-disciplinary Conference on Reinforcement Learning and Decision Making (RLDM), 2019
Learning What to Remember with Online Policy Gradient Over a Reservoir
Kenny Young, Richard S. Sutton
NeurIPS Workshop on Reinforcement Learning under Partial Observability, 2018
Comparing Direct and Indirect Temporal-Difference Methods for Estimating the Variance of the Return
Craig Sherstan, Brendan Bennett, Dylan R. Ashley, Kenny Young, Adam White, Martha White, Richard S. Sutton
Conference on Uncertainty in Artificial Intelligence (UAI), 2018
Direct Estimation of the Variance of the λ-Return with Temporal-Difference Methods
Craig Sherstan, Brendan Bennett, Kenny Young, Dylan R. Ashley, Adam White, Martha White, Richard S. Sutton
The Multi-disciplinary Conference on Reinforcement Learning and Decision Making (RLDM), 2017
Neurohex: A Deep Q-learning Hex Agent
Kenny Young, Ryan Hayward, Gautham Vasan
IJCAI Computer Games Workshop, 2016
Kenny Young, Ryan Hayward
International Computer Games Association Conference (ICGA), 2016