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Conference and Workshop Papers
- 2024
[c8]Aditya A. Ramesh, Kenny John Young, Louis Kirsch, Jürgen Schmidhuber:
Sequence Compression Speeds Up Credit Assignment in Reinforcement Learning. ICML 2024- 2023
- [c7]Kenny John Young, Aditya A. Ramesh, Louis Kirsch, Jürgen Schmidhuber:
The Benefits of Model-Based Generalization in Reinforcement Learning. ICML 2023: 40254-40276 - 2022
- [c6]Kenny Young:
Hindsight Network Credit Assignment: Efficient Credit Assignment in Networks of Discrete Stochastic Units. AAAI 2022: 8919-8926 - [c5]Tian Tian, Kenny Young, Richard S. Sutton:
Doubly-Asynchronous Value Iteration: Making Value Iteration Asynchronous in Actions. NeurIPS 2022 - 2019
- [c4]Kenny Young, Baoxiang Wang, Matthew E. Taylor:
Metatrace Actor-Critic: Online Step-Size Tuning by Meta-gradient Descent for Reinforcement Learning Control. IJCAI 2019: 4185-4191 - 2018
- [c3]Craig Sherstan, Dylan R. Ashley, Brendan Bennett, Kenny Young, Adam White, Martha White, Richard S. Sutton:
Comparing Direct and Indirect Temporal-Difference Methods for Estimating the Variance of the Return. UAI 2018: 63-72 - 2016
- [c2]Kenny Young, Ryan B. Hayward:
A Reverse Hex Solver. Computers and Games 2016: 137-148 - [c1]Kenny Young, Gautham Vasan, Ryan Hayward:
NeuroHex: A Deep Q-learning Hex Agent. CGW@IJCAI 2016: 3-18
Informal and Other Publications
- 2024
- [i14]Aditya A. Ramesh, Kenny Young, Louis Kirsch, Jürgen Schmidhuber:
Sequence Compression Speeds Up Credit Assignment in Reinforcement Learning. CoRR abs/2405.03878 (2024) - 2023
- [i13]Kenny Young, Richard S. Sutton:
Iterative Option Discovery for Planning, by Planning. CoRR abs/2310.01569 (2023) - 2022
- [i12]Tian Tian, Kenny Young, Richard S. Sutton:
Doubly-Asynchronous Value Iteration: Making Value Iteration Asynchronous in Actions. CoRR abs/2207.01613 (2022) - [i11]Kenny Young, Aditya A. Ramesh, Louis Kirsch, Jürgen Schmidhuber:
The Benefits of Model-Based Generalization in Reinforcement Learning. CoRR abs/2211.02222 (2022) - 2021
- [i10]Kenny Young:
Hindsight Network Credit Assignment: Efficient Credit Assignment in Networks of Discrete Stochastic Units. CoRR abs/2110.07700 (2021) - 2020
- [i9]Kenny Young, Richard S. Sutton:
Understanding the Pathologies of Approximate Policy Evaluation when Combined with Greedification in Reinforcement Learning. CoRR abs/2010.15268 (2020) - [i8]Kenny Young:
Hindsight Network Credit Assignment. CoRR abs/2011.12351 (2020) - 2019
- [i7]Kenny Young, Tian Tian:
MinAtar: An Atari-inspired Testbed for More Efficient Reinforcement Learning Experiments. CoRR abs/1903.03176 (2019) - [i6]Kenny Young:
Variance Reduced Advantage Estimation with δ Hindsight Credit Assignment. CoRR abs/1911.08362 (2019) - 2018
- [i5]Craig Sherstan, Brendan Bennett, Kenny Young, Dylan R. Ashley
, Adam White, Martha White, Richard S. Sutton:
Directly Estimating the Variance of the λ-Return Using Temporal-Difference Methods. CoRR abs/1801.08287 (2018) - [i4]Kenny Young, Baoxiang Wang, Matthew E. Taylor:
Metatrace: Online Step-size Tuning by Meta-gradient Descent for Reinforcement Learning Control. CoRR abs/1805.04514 (2018) - [i3]Kenny J. Young, Richard S. Sutton, Shuo Yang:
Integrating Episodic Memory into a Reinforcement Learning Agent using Reservoir Sampling. CoRR abs/1806.00540 (2018) - 2017
- [i2]Kenny Young, Ryan B. Hayward:
A Reverse Hex Solver. CoRR abs/1707.00627 (2017) - 2016
- [i1]Kenny Young, Ryan Hayward, Gautham Vasan:
Neurohex: A Deep Q-learning Hex Agent. CoRR abs/1604.07097 (2016)
Coauthor Index
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