Dylan R. Ashley

31 papers A* 3A 2B 1C 1Journal 23Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Efficient Morphology-Control Co-Design via Stackelberg Proximal Policy Optimization. CoRR Yanning Dai, Yuhui Wang, Dylan R. Ashley, Jürgen Schmidhuber
2026	J	`jnl`	RACAS: Controlling Diverse Robots With a Single Agentic System. CoRR Dylan R. Ashley, Jan Przepióra, Yimeng Chen, Ali Abualsaud, Nurzhan Yesmagambet, Shinkyu Park, Eric Feron, Jürgen Schmidhuber
2025	A*	`conf`	Agent-as-a-Judge: Evaluate Agents with Agents. ICML Mingchen Zhuge, Changsheng Zhao, Dylan R. Ashley, Wenyi Wang, Dmitrii Khizbullin, Yunyang Xiong, Zechun Liu, Ernie Chang, Raghuraman Krishnamoorthi, Yuandong Tian, Yangyang Shi, Vikas Chandra, Jürgen Schmidhuber
2025	J	`jnl`	Mindstorms in Natural Language-Based Societies of Mind. Comput. Vis. Media Mingchen Zhuge, Haozhe Liu, Francesco Faccio, Dylan R. Ashley, Róbert Csordás, Anand Gopalakrishnan, Abdullah Hamdi, Hasan Abed Al Kader Hammoud, Vincent Herrmann, Kazuki Irie, Louis Kirsch, Bing Li, Guohao Li, Shuming Liu, Jinjie Mai, Piotr Piekos, Aditya A. Ramesh, Imanol Schlag, Weimin Shi, Aleksandar Stanic, Wenyi Wang, Yuhui Wang, Mengmeng Xu, Deng-Ping Fan, Bernard Ghanem, Jürgen Schmidhuber
2025	J	`jnl`	On the Convergence and Stability of Upside-Down Reinforcement Learning, Goal-Conditioned Supervised Learning, and Online Decision Transformers. CoRR Miroslav Strupl, Oleg Szehr, Francesco Faccio, Dylan R. Ashley, Rupesh Kumar Srivastava, Jürgen Schmidhuber
2025	J	`jnl`	On the Distillation of Stories for Transferring Narrative Arcs in Collections of Independent Media. IEEE Trans. Pattern Anal. Mach. Intell. Dylan R. Ashley, Vincent Herrmann, Zachary Friggstad, Jürgen Schmidhuber
2025	A*	`conf`	Scaling Value Iteration Networks to 5000 Layers for Extreme Long-Term Planning. ICML Yuhui Wang, Qingyuan Wu, Dylan R. Ashley, Francesco Faccio, Weida Li, Chao Huang, Jürgen Schmidhuber
2025	A	`conf`	Towards an Extremely Robust Baby Robot With Rich Interaction Ability for Advanced Machine Learning Algorithms. IROS Mohannad Alhakami, Dylan R. Ashley, Joel Dunham, Yanning Dai, Francesco Faccio, Eric Feron, Jürgen Schmidhuber
2025	J	`jnl`	Upside Down Reinforcement Learning with Policy Generators. CoRR Jacopo Di Ventura, Dylan R. Ashley, Vincent Herrmann, Francesco Faccio, Jürgen Schmidhuber
2024	J	`jnl`	Agent-as-a-Judge: Evaluate Agents with Agents. CoRR Mingchen Zhuge, Changsheng Zhao, Dylan R. Ashley, Wenyi Wang, Dmitrii Khizbullin, Yunyang Xiong, Zechun Liu, Ernie Chang, Raghuraman Krishnamoorthi, Yuandong Tian, Yangyang Shi, Vikas Chandra, Jürgen Schmidhuber
2024	J	`jnl`	Automatic Album Sequencing. CoRR Vincent Herrmann, Dylan R. Ashley, Jürgen Schmidhuber
2024	J	`jnl`	How to Correctly do Semantic Backpropagation on Language-based Agentic Systems. CoRR Wenyi Wang, Hisham Abdullah Alyahya, Dylan R. Ashley, Oleg Serikov, Dmitrii Khizbullin, Francesco Faccio, Jürgen Schmidhuber
2024	J	`jnl`	Scaling Value Iteration Networks to 5000 Layers for Extreme Long-Term Planning. CoRR Yuhui Wang, Qingyuan Wu, Weida Li, Dylan R. Ashley, Francesco Faccio, Chao Huang, Jürgen Schmidhuber
2024	J	`jnl`	Towards a Robust Soft Baby Robot With Rich Interaction Ability for Advanced Machine Learning Algorithms. CoRR Mohannad Alhakami, Dylan R. Ashley, Joel Dunham, Francesco Faccio, Eric Feron, Jürgen Schmidhuber
2023	J	`jnl`	Mindstorms in Natural Language-Based Societies of Mind. CoRR Mingchen Zhuge, Haozhe Liu, Francesco Faccio, Dylan R. Ashley, Róbert Csordás, Anand Gopalakrishnan, Abdullah Hamdi, Hasan Abed Al Kader Hammoud, Vincent Herrmann, Kazuki Irie, Louis Kirsch, Bing Li, Guohao Li, Shuming Liu, Jinjie Mai, Piotr Piekos, Aditya A. Ramesh, Imanol Schlag, Weimin Shi, Aleksandar Stanic, Wenyi Wang, Yuhui Wang, Mengmeng Xu, Deng-Ping Fan, Bernard Ghanem, Jürgen Schmidhuber
2023	J	`jnl`	The Languini Kitchen: Enabling Language Modelling Research at Different Scales of Compute. CoRR Aleksandar Stanic, Dylan R. Ashley, Oleg Serikov, Louis Kirsch, Francesco Faccio, Jürgen Schmidhuber, Thomas Hofmann, Imanol Schlag
2022	J	`jnl`	All You Need Is Supervised Learning: From Imitation Learning to Meta-RL With Upside Down RL. CoRR Kai Arulkumaran, Dylan R. Ashley, Jürgen Schmidhuber, Rupesh Kumar Srivastava
2022	J	`jnl`	Learning Relative Return Policies With Upside-Down Reinforcement Learning. CoRR Dylan R. Ashley, Kai Arulkumaran, Jürgen Schmidhuber, Rupesh Kumar Srivastava
2022	J	`jnl`	On Narrative Information and the Distillation of Stories. CoRR Dylan R. Ashley, Vincent Herrmann, Zachary Friggstad, Jürgen Schmidhuber
2022	A*	`conf`	Reward-Weighted Regression Converges to a Global Optimum. AAAI Miroslav Strupl, Francesco Faccio, Dylan R. Ashley, Rupesh Kumar Srivastava, Jürgen Schmidhuber
2022	J	`jnl`	Upside-Down Reinforcement Learning Can Diverge in Stochastic Environments With Episodic Resets. CoRR Miroslav Strupl, Francesco Faccio, Dylan R. Ashley, Jürgen Schmidhuber, Rupesh Kumar Srivastava
2021	J	`jnl`	Automatic Embedding of Stories Into Collections of Independent Media. CoRR Dylan R. Ashley, Vincent Herrmann, Zachary Friggstad, Kory W. Mathewson, Jürgen Schmidhuber
2021	J	`jnl`	Back to Square One: Superhuman Performance in Chutes and Ladders Through Deep Neural Networks and Tree Search. CoRR Dylan R. Ashley, Anssi Kanervisto, Brendan Bennett
2021	J	`jnl`	Does Standard Backpropagation Forget Less Catastrophically Than Adam? CoRR Dylan R. Ashley, Sina Ghiassian, Richard S. Sutton
2021	J	`jnl`	Reward-Weighted Regression Converges to a Global Optimum. CoRR Miroslav Strupl, Francesco Faccio, Dylan R. Ashley, Rupesh Kumar Srivastava, Jürgen Schmidhuber
2020	J	`jnl`	Universal Successor Features for Transfer Reinforcement Learning. CoRR Chen Ma, Dylan R. Ashley, Junfeng Wen, Yoshua Bengio
2019	C	`conf`	Learning to Select Mates in Evolving Non-playable Characters. CoG Dylan R. Ashley, Valliappa Chockalingam, Braedy Kuzma, Vadim Bulitko
2019	—	`conf`	Learning to select mates in artificial life. GECCO (Companion) Dylan R. Ashley, Valliappa Chockalingam, Braedy Kuzma, Vadim Bulitko
2018	A	`conf`	Comparing Direct and Indirect Temporal-Difference Methods for Estimating the Variance of the Return. UAI Craig Sherstan, Dylan R. Ashley, Brendan Bennett, Kenny Young, Adam White, Martha White, Richard S. Sutton
2018	J	`jnl`	Directly Estimating the Variance of the λ-Return Using Temporal-Difference Methods. CoRR Craig Sherstan, Brendan Bennett, Kenny Young, Dylan R. Ashley, Adam White, Martha White, Richard S. Sutton
2018	B	`conf`	The Alberta Workloads for the SPEC CPU 2017 Benchmark Suite. ISPASS José Nelson Amaral, Edson Borin, Dylan R. Ashley, Caian Benedicto, Elliot Colp, Joao Henrique Stange Hoffmam, Marcus Karpoff, Erick Ochoa, Morgan Redshaw, Raphael Ernani Rodrigues