Nathaniel D. Daw

Publication Activity (10 Years)

Years Active: 2000-2024
Publications (10 Years): 24

Top Topics

Reinforcement Learning

Cognitive Models

Hierarchical Bayesian

Top Venues

PLoS Comput. Biol.

J. Cogn. Neurosci.

Publications

Carlos G. Correa, Thomas L. Griffiths, Nathaniel D. Daw
Program-Based Strategy Induction for Reinforcement Learning. CoRR (2024)
Sreejan Kumar, Ishita Dasgupta, Nathaniel D. Daw, Jonathan D. Cohen, Thomas L. Griffiths
Disentangling Abstraction from Statistical Pattern Matching in Human and Machine Learning. PLoS Comput. Biol. 19 (8) (2023)
Carlos G. Correa, Mark K. Ho, Frederick Callaway, Nathaniel D. Daw, Thomas L. Griffiths
Humans decompose tasks by trading off utility and computational cost. PLoS Comput. Biol. 19 (6) (2023)
Maria K. Eckstein, Christopher Summerfield, Nathaniel D. Daw, Kevin J. Miller
Predictive and Interpretable: Combining Artificial Neural Networks and Classic Cognitive Models to Understand Human Learning and Decision Making. CogSci (2023)
Carlos G. Correa, Sophia Sanborn, Mark K. Ho, Frederick Callaway, Nathaniel D. Daw, Thomas L. Griffiths
Exploring the hierarchical structure of human plans via program generation. CoRR (2023)
Ham Huang, Ivan Grahek, Laura Bustamante, Nathaniel D. Daw, Andrew Caplin, Sebastian Musslick
Leveraging psychometrics of rational inattention to estimate individual differences in the capacity for cognitive control. CogSci (2022)
Sreejan Kumar, Carlos G. Correa, Ishita Dasgupta, Raja Marjieh, Michael Y. Hu, Robert D. Hawkins, Jonathan D. Cohen, Nathaniel D. Daw, Karthik Narasimhan, Tom Griffiths
Using natural language and program abstractions to instill human inductive biases in machines. NeurIPS (2022)
Sreejan Kumar, Ishita Dasgupta, Raja Marjieh, Nathaniel D. Daw, Jonathan D. Cohen, Thomas L. Griffiths
Disentangling Abstraction from Statistical Pattern Matching in Human and Machine Learning. CoRR (2022)
Sreejan Kumar, Carlos G. Correa, Ishita Dasgupta, Raja Marjieh, Michael Y. Hu, Robert D. Hawkins, Nathaniel D. Daw, Jonathan D. Cohen, Karthik Narasimhan, Thomas L. Griffiths
Using Natural Language and Program Abstractions to Instill Human Inductive Biases in Machines. CoRR (2022)
Carlos G. Correa, Mark K. Ho, Frederick Callaway, Nathaniel D. Daw, Thomas L. Griffiths
Humans decompose tasks by trading off utility and computational cost. CoRR (2022)
Sreejan Kumar, Ishita Dasgupta, Jonathan D. Cohen, Nathaniel D. Daw, Thomas L. Griffiths
Meta-Learning of Structured Task Distributions in Humans and Machines. ICLR (2021)
Karin Foerde, Nathaniel D. Daw, Teresa Rufin, B. Timothy Walsh, Daphna Shohamy, Joanna E. Steinglass
Deficient Goal-Directed Control in a Population Characterized by Extreme Goal Pursuit. J. Cogn. Neurosci. 33 (3) (2021)
Sreejan Kumar, Ishita Dasgupta, Jonathan D. Cohen, Nathaniel D. Daw, Thomas L. Griffiths
Meta-Learning of Compositional Task Distributions in Humans and Machines. CoRR (2020)
Payam Piray, Nathaniel D. Daw
A simple model for learning in volatile environments. PLoS Comput. Biol. 16 (7) (2020)
Sagi Jaffe-Dax, Alex M. Boldin, Nathaniel D. Daw, Lauren L. Emberson
A Computational Role for Top-Down Modulation from Frontal Cortex in Infancy. J. Cogn. Neurosci. 32 (3) (2020)
Payam Piray, Amir Dezfouli, Tom Heskes, Michael J. Frank, Nathaniel D. Daw
Hierarchical Bayesian inference for concurrent model fitting and comparison for group studies. PLoS Comput. Biol. 15 (6) (2019)
Laura Bustamante, Augustus Baker, Allison Burton, Amitai Shenhav, Chloe Hoeber, Nathaniel D. Daw, Jonathan Cohen
Novel methods for measuring the cost of cognitive control in a patch foraging task and a demand selection task with Stroop. CogSci (2018)
Elyse H. Norton, Stephen M. Fleming, Nathaniel D. Daw, Michael S. Landy
Suboptimal Criterion Learning in Static and Dynamic Environments. PLoS Comput. Biol. 13 (1) (2017)
Gary Kane, Aaron M. Bornstein, Robert Wilson, Amitai Shenhav, Nathaniel D. Daw, Jonathan Cohen
Mechanisms of overharvesting in patch foraging. CogSci (2017)
Sagi Jaffe-Dax, Alex M. Boldin, Nathaniel D. Daw, Lauren L. Emberson
Pre-term infants exhibit impaired prediction and learning in Audio-Visual association paradigm. CogSci (2017)
Jennifer Lenow, Nathaniel D. Daw, Elizabeth Phelps
Intolerance to uncertainty is associated with diminished exploration. CogSci (2017)
Evan M. Russek, Ida Momennejad, Matthew Botvinick, Samuel J. Gershman, Nathaniel D. Daw
Predictive representations can link model-based reinforcement learning to model-free mechanisms. PLoS Comput. Biol. 13 (9) (2017)
Andra Geana, Robert Wilson, Nathaniel D. Daw, Jonathan Cohen
Boredom, Information-Seeking and Exploration. CogSci (2016)
Andra Geana, Robert Wilson, Nathaniel D. Daw, Jonathan Cohen
Information-Seeking, Learning and the Marginal Value Theorem: A Normative Approach to Adaptive Exploration. CogSci (2016)
A. Ross Otto, Anya Skatova, Seth Madlon-Kay, Nathaniel D. Daw
Cognitive Control Predicts Use of Model-based Reinforcement Learning. J. Cogn. Neurosci. 27 (2) (2015)
A. Ross Otto, Anya Skatova, Seth Madlon-Kay, Nathaniel D. Daw
Cognitive Control Mode Predicts Behavioral Expression of Model-Based Reinforcement-Learning. CogSci (2014)
Mattia Rigotti, Omri Barak, Melissa R. Warden, Xiao-Jing Wang, Nathaniel D. Daw, Earl K. Miller, Stefano Fusi
The importance of mixed selectivity in complex cognitive tasks. Nat. 497 (7451) (2013)
Aaron M. Bornstein, Nathaniel D. Daw
Cortical and Hippocampal Correlates of Deliberation during Model-Based Decisions for Rewards in Humans. PLoS Comput. Biol. 9 (12) (2013)
Seth Madlon-Kay, Bijan Pesaran, Nathaniel D. Daw
Action selection in multi-effector decision making. NeuroImage 70 (2013)
Hang Zhang, Nathaniel D. Daw, Laurence T. Maloney
Testing Whether Humans Have an Accurate Model of Their Own Motor Uncertainty in a Speeded Reaching Task. PLoS Comput. Biol. 9 (5) (2013)
Kenji Doya, John P. O'Doherty, Alexandre Pouget, Peter Bossaerts, Nathaniel D. Daw, Yael Niv
Neural Computations Supporting Cognition: Rumelhart Prize Symposium in Honor of Peter Dayan. CogSci (2012)
Bradley C. Love, John P. Spencer, Nathaniel D. Daw, John P. O'Doherty
Moving Beyond Where and What to How: Using Models and fMRI to Understand Brain-Behavior Relations. CogSci (2011)
Dylan A. Simon, Nathaniel D. Daw
Environmental statistics and the trade-off between model-based and TD learning in humans. NIPS (2011)
Nicholas J. Gustafson, Nathaniel D. Daw
Grid Cells, Place Cells, and Geodesic Generalization for Spatial Reinforcement Learning. PLoS Comput. Biol. 7 (10) (2011)
Tom Schonberg, John P. O'Doherty, Daphna Joel, Rivka Inzelberg, Yoram Segev, Nathaniel D. Daw
Selective impairment of prediction error signaling in human dorsolateral but not ventral striatum in Parkinson's disease patients: evidence from a model-based fMRI study. NeuroImage 49 (1) (2010)
Nathaniel D. Daw, Aaron C. Courville
The rat as particle filter. NIPS (2007)
Nathaniel D. Daw, Aaron C. Courville, David S. Touretzky
Representation and Timing in Theories of the Dopamine System. Neural Comput. 18 (7) (2006)
Peter Dayan, Yael Niv, Ben Seymour, Nathaniel D. Daw
The misbehavior of value and the discipline of the will. Neural Networks 19 (8) (2006)
Yael Niv, Nathaniel D. Daw, Peter Dayan
How fast to work: Response vigor, motivation and tonic dopamine. NIPS (2005)
Aaron C. Courville, Nathaniel D. Daw, David S. Touretzky
Similarity and Discrimination in Classical Conditioning: A Latent Variable Account. NIPS (2004)
Aaron C. Courville, Nathaniel D. Daw, Geoffrey J. Gordon, David S. Touretzky
Model Uncertainty in Classical Conditioning. NIPS (2003)
Rudolf N. Cardinal, Nathaniel D. Daw, Trevor W. Robbins, Barry J. Everitt
Local analysis of behaviour in the adjusting-delay task for assessing choice of delayed reinforcement. Neural Networks 15 (4-6) (2002)
Nathaniel D. Daw, David S. Touretzky
Long-Term Reward Prediction in TD Models of the Dopamine System. Neural Comput. 14 (11) (2002)
Nathaniel D. Daw, Sham M. Kakade, Peter Dayan
Opponent interactions between serotonin and dopamine. Neural Networks 15 (4-6) (2002)
Nathaniel D. Daw, Aaron C. Courville, David S. Touretzky
Timing and Partial Observability in the Dopamine System. NIPS (2002)
Nathaniel D. Daw, David S. Touretzky
Operant behavior suggests attentional gating of dopamine system inputs. Neurocomputing (2001)
Nathaniel D. Daw, Seth Copen Goldstein, Dennis Strelow
Embedded Compilation for Multimedia Applications. FCCM (2000)
Nathaniel D. Daw, David S. Touretzky
Behavioral considerations suggest an average reward TD model of the dopamine system. Neurocomputing (2000)