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Dylan R. Ashley
Dylan R. Ashley
Ph.D. Student, Dalle Molle Institute for Artificial Intelligence Research (IDSIA USI-SUPSI)
Verified email at dylanashley.io - Homepage
Title
Cited by
Cited by
Year
Mindstorms in natural language-based societies of mind
M Zhuge, H Liu, F Faccio, DR Ashley, R Csordás, A Gopalakrishnan, ...
arXiv preprint arXiv:2305.17066, 2023
322023
Universal successor features for transfer reinforcement learning
C Ma, DR Ashley, J Wen, Y Bengio
arXiv preprint arXiv:2001.04025, 2020
212020
The alberta workloads for the spec cpu 2017 benchmark suite
JN Amaral, E Borin, DR Ashley, C Benedicto, E Colp, JHS Hoffmam, ...
2018 IEEE International Symposium on Performance Analysis of Systems and …, 2018
192018
Comparing Direct and Indirect Temporal-Difference Methods for Estimating the Variance of the Return.
C Sherstan, DR Ashley, B Bennett, K Young, A White, M White, RS Sutton
UAI, 63-72, 2018
192018
Directly estimating the variance of the {\lambda}-return using temporal-difference methods
C Sherstan, B Bennett, K Young, DR Ashley, A White, M White, RS Sutton
arXiv preprint arXiv:1801.08287, 2018
162018
Upside-down reinforcement learning can diverge in stochastic environments with episodic resets
M Štrupl, F Faccio, DR Ashley, J Schmidhuber, RK Srivastava
arXiv preprint arXiv:2205.06595, 2022
112022
All you need is supervised learning: From imitation learning to meta-rl with upside down rl
K Arulkumaran, DR Ashley, J Schmidhuber, RK Srivastava
arXiv preprint arXiv:2202.11960, 2022
82022
Does the Adam Optimizer Exacerbate Catastrophic Forgetting?
DR Ashley, S Ghiassian, RS Sutton
arXiv preprint arXiv:2102.07686, 2021
42021
Learning to select mates in evolving non-playable characters
DR Ashley, V Chockalingam, B Kuzma, V Bulitko
2019 IEEE Conference on Games (CoG), 1-8, 2019
42019
Reward-weighted regression converges to a global optimum
M Štrupl, F Faccio, DR Ashley, RK Srivastava, J Schmidhuber
Proceedings of the AAAI Conference on Artificial Intelligence 36 (8), 8361-8369, 2022
32022
The Languini Kitchen: Enabling Language Modelling Research at Different Scales of Compute
A Stanić, D Ashley, O Serikov, L Kirsch, F Faccio, J Schmidhuber, ...
arXiv preprint arXiv:2309.11197, 2023
22023
Learning relative return policies with upside-down reinforcement learning
DR Ashley, K Arulkumaran, J Schmidhuber, RK Srivastava
arXiv preprint arXiv:2202.12742, 2022
12022
Learning to select mates in artificial life
DR Ashley, V Chockalingam, B Kuzma, V Bulitko
Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2019
12019
Towards a Robust Soft Baby Robot With Rich Interaction Ability for Advanced Machine Learning Algorithms
M Alhakami, DR Ashley, J Dunham, F Faccio, E Feron, J Schmidhuber
arXiv preprint arXiv:2404.08093, 2024
2024
On Narrative Information and the Distillation of Stories
DR Ashley, V Herrmann, Z Friggstad, J Schmidhuber
arXiv preprint arXiv:2211.12423, 2022
2022
dylanashley/story-distiller
DR Ashley, V Herrmann, Z Friggstad, J Schmidhuber
Github, 2022
2022
Automatic Embedding of Stories Into Collections of Independent Media
DR Ashley, V Herrmann, Z Friggstad, KW Mathewson, J Schmidhuber
arXiv preprint arXiv:2111.02216, 2021
2021
Back to Square One: Superhuman Performance in Chutes and Ladders Through Deep Neural Networks and Tree Search
D Ashley, A Kanervisto, B Bennett
arXiv preprint arXiv:2104.00698, 2021
2021
Understanding Forgetting in Artificial Neural Networks
DR Ashley
2020
On the Distillation of Stories for Transferring Narrative Arcs in Collections of Independent Media
DR Ashley, V Herrmann, Z Friggstad, J Schmidhuber, AI Initiative
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