Arbitration between controlled and impulsive choices. - Marcos Economides; Marc Guitart-Masip; Zeb Kurth-Nelson; Raymond J. Dolan (NeuroImage, 2015)

Model-Based Reasoning in Humans Becomes Automatic with Training. - Marcos Economides; Zeb Kurth-Nelson; Annika Lübbert; Marc Guitart-Masip; Raymond J. Dolan (PLoS Comput. Biol., 2015)

Learning to reinforcement learn. - Jane Wang 001; Zeb Kurth-Nelson; Hubert Soyer; Joel Z. Leibo; Dhruva Tirumala; Rémi Munos; Charles Blundell; Dharshan Kumaran; Matt M. Botvinick (CogSci, 2017)

Local striatal reward signals can be predicted from corticostriatal connectivity. - Peter Smittenaar; Zeb Kurth-Nelson; Siawoosh Mohammadi; Nikolaus Weiskopf; Raymond J. Dolan (NeuroImage, 2017)

Episodic Control through Meta-Reinforcement Learning. - Samuel Ritter; Jane X. Wang; Zeb Kurth-Nelson; Matthew M. Botvinick (CogSci, 2018)

Been There, Done That: Meta-Learning with Episodic Recall. - Samuel Ritter; Jane X. Wang; Zeb Kurth-Nelson; Siddhant M. Jayakumar; Charles Blundell; Razvan Pascanu; Matthew M. Botvinick (ICML, 2018)

Causal Reasoning from Meta-reinforcement Learning. - Ishita Dasgupta 001; Jane X. Wang; Silvia Chiappa; Jovana Mitrovic; Pedro A. Ortega; David Raposo; Edward Hughes 001; Peter W. Battaglia; Matthew M. Botvinick; Zeb Kurth-Nelson (CoRR, 2019)

Meta-learning of Sequential Strategies. - Pedro A. Ortega; Jane X. Wang; Mark Rowland 001; Tim Genewein; Zeb Kurth-Nelson; Razvan Pascanu; Nicolas Heess; Joel Veness; Alexander Pritzel; Pablo Sprechmann; Siddhant M. Jayakumar; Tom McGrath; et al. (CoRR, 2019)

Deep Reinforcement Learning and its Neuroscientific Implications. - Matthew M. Botvinick; Jane X. Wang; Will Dabney; Kevin J. Miller; Zeb Kurth-Nelson (CoRR, 2020)

A distributional code for value in dopamine-based reinforcement learning. - Will Dabney; Zeb Kurth-Nelson; Naoshige Uchida; Clara Kwon Starkweather; Demis Hassabis; Rémi Munos; Matthew M. Botvinick (Nat., 2020)

Alchemy: A benchmark and analysis toolkit for meta-reinforcement learning agents. - Jane Wang 001; Michael King; Nicolas Porcel; Zeb Kurth-Nelson; Tina Zhu; Charles Deck; Peter Choy; Mary Cassin; Malcolm Reynolds; H. Francis Song; Gavin Buttimore; David P. Reichert; et al. (NeurIPS Datasets and Benchmarks, 2021)

Alchemy: A structured task distribution for meta-reinforcement learning. - Jane X. Wang; Michael King; Nicolas Porcel; Zeb Kurth-Nelson; Tina Zhu; Charlie Deck; Peter Choy; Mary Cassin; Malcolm Reynolds; H. Francis Song; Gavin Buttimore; David P. Reichert; et al. (CoRR, 2021)

How to Learn and Represent Abstractions: An Investigation using Symbolic Alchemy. - Badr AlKhamissi; Akshay Srinivasan; Zeb Kurth-Nelson; Sam Ritter (CoRR, 2021)

Cognitive Model Discovery via Disentangled RNNs. - Kevin J. Miller; Maria K. Eckstein; Matt M. Botvinick; Zeb Kurth-Nelson (NeurIPS, 2023)

The Ethics of Advanced AI Assistants. - Iason Gabriel; Arianna Manzini; Geoff Keeling; Lisa Anne Hendricks; Verena Rieser; Hasan Iqbal; Nenad Tomasev; Ira Ktena; Zachary Kenton; Mikel Rodriguez; Seliem El-Sayed; Sasha Brown; et al. (CoRR, 2024)

Increasing happiness through conversations with artificial intelligence. - Joseph Heffner; Chongyu Qin; Martin J. Chadwick; Chris Knutsen; Christopher Summerfield; Zeb Kurth-Nelson; Robb B. Rutledge (CoRR, 2025)

Technological folie à deux: Feedback Loops Between AI Chatbots and Mental Illness. - Sebastian Dohnány; Zeb Kurth-Nelson; Eleanor Spens; Lennart Luettgau; Alastair Reid 002; Iason Gabriel; Christopher Summerfield; Murray Shanahan; Matthew M. Nour (CoRR, 2025)