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 | 48 | 2023 |
Universal successor features for transfer reinforcement learning C Ma, DR Ashley, J Wen, Y Bengio arXiv preprint arXiv:2001.04025, 2020 | 26 | 2020 |
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 | 20 | 2018 |
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 | 19 | 2018 |
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 | 17 | 2018 |
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 | 10 | 2022 |
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 | 8 | 2022 |
Does the Adam Optimizer Exacerbate Catastrophic Forgetting? DR Ashley, S Ghiassian, RS Sutton arXiv preprint arXiv:2102.07686, 2021 | 4 | 2021 |
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 | 4 | 2019 |
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 | 3 | 2023 |
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 | 3 | 2022 |
Learning relative return policies with upside-down reinforcement learning DR Ashley, K Arulkumaran, J Schmidhuber, RK Srivastava arXiv preprint arXiv:2202.12742, 2022 | 1 | 2022 |
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 | 1 | 2019 |
Scaling Value Iteration Networks to 5000 Layers for Extreme Long-Term Planning Y Wang, Q Wu, W Li, DR Ashley, F Faccio, C Huang, J Schmidhuber arXiv preprint arXiv:2406.08404, 2024 | | 2024 |
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 |