David Abel is a Senior Research Scientist at DeepMind on the Agency team, and an Honorary Fellow at the University of Edinburgh. His research blends computer science and philosophy, exploring foundational questions about reinforcement learning, definitions, and the nature of agency.

Featured References

Plasticity as the Mirror of Empowerment
David Abel, Michael Bowling, André Barreto, Will Dabney, Shi Dong, Steven Hansen, Anna Harutyunyan, Khimya Khetarpal, Clare Lyle, Razvan Pascanu, Georgios Piliouras, Doina Precup, Jonathan Richens, Mark Rowland, Tom Schaul, Satinder Singh

A Definition of Continual RL
David Abel, André Barreto, Benjamin Van Roy, Doina Precup, Hado van Hasselt, Satinder Singh

Agency is Frame-Dependent
David Abel, André Barreto, Michael Bowling, Will Dabney, Shi Dong, Steven Hansen, Anna Harutyunyan, Khimya Khetarpal, Clare Lyle, Razvan Pascanu, Georgios Piliouras, Doina Precup, Jonathan Richens, Mark Rowland, Tom Schaul, Satinder Singh

On the Expressivity of Markov Reward
David Abel, Will Dabney, Anna Harutyunyan, Mark Ho, Michael Littman, Doina Precup, Satinder Singh — Outstanding Paper Award, NeurIPS 2021

Additional References

• Bidirectional Communication Theory — Marko 1973
• Causality, Feedback and Directed Information — Massey 1990
• The Big World Hypothesis — Javed et al. 2024
• Loss of plasticity in deep continual learning — Dohare et al. 2024
• Three Dogmas of Reinforcement Learning — Abel 2024
• Explaining dopamine through prediction errors and beyond — Gershman et al. 2024
• David Abel Google Scholar
• David Abel personal website

Recorded at Reinforcement Learning Conference 2025 at University of Alberta, Edmonton Alberta Canada.

Featured References

Lecture on the Oak Architecture, Rich Sutton

Alberta Plan, Rich Sutton with Mike Bowling and Patrick Pilarski

Additional References

• Jacob Beck on Google Scholar
• Alex Goldie on Google Scholar
• Cornelius Braun on Google Scholar
• Reinforcement Learning Conference

We caught up with the RLC Outstanding Paper award winners for your listening pleasure.

Recorded on location at Reinforcement Learning Conference 2025, at University of Alberta, in Edmonton Alberta Canada in August 2025.

Featured References

Empirical Reinforcement Learning Research
Mitigating Suboptimality of Deterministic Policy Gradients in Complex Q-functions
Ayush Jain, Norio Kosaka, Xinhu Li, Kyung-Min Kim, Erdem Biyik, Joseph J Lim

Applications of Reinforcement Learning
WOFOSTGym: A Crop Simulator for Learning Annual and Perennial Crop Management Strategies
William Solow, Sandhya Saisubramanian, Alan Fern

Emerging Topics in Reinforcement Learning
Towards Improving Reward Design in RL: A Reward Alignment Metric for RL Practitioners
Calarina Muslimani, Kerrick Johnstonbaugh, Suyog Chandramouli, Serena Booth, W. Bradley Knox, Matthew E. Taylor

Scientific Understanding in Reinforcement Learning
Multi-Task Reinforcement Learning Enables Parameter Scaling
Reginald McLean, Evangelos Chatzaroulas, J K Terry, Isaac Woungang, Nariman Farsad, Pablo Samuel Castro