Gershman, Samuel J.

Building machines that learn and think like people

Lake, B. M., Ullman, T. D., Tenenbaum, J. B., & Gershman, S. J. (2017) · Behavioral and Brain Sciences

Psychiatry, Mental Health, NeuroscienceAI-based Problem Solving and Planning

Cited by 2,550

Building Machines That Learn and Think Like People

Lake, B. M., Ullman, T. D., Tenenbaum, J. B., & Gershman, S. J. (2016) · arXiv

Psychiatry, Mental Health, NeuroscienceAI-based Problem Solving and Planning

Cited by 2,550

Model-based influences on humans’ choices and striatal prediction errors

Daw, N. D., Gershman, S. J., Seymour, B., Dayan, P., & Dolan, R. J. (2011) · Neuron

Neural and Behavioral Psychology StudiesNeurotransmitter Receptor Influence on Behavior

Cited by 1,779

The hippocampus as a predictive map

Stachenfeld, K. L., Botvinick, M. M., & Gershman, S. J. (2017) · Nature Neuroscience

Memory and Neural MechanismsSpatial Cognition and Navigation

Cited by 1,000

Accountability of AI Under the Law: The Role of Explanation

Doshi-Velez, F., Kortz, M., Budish, R., Bavitz, C., Gershman, S. J., O'Brien, D., Scott, K., Shieber, S., Waldo, J., Weinberger, D., et al. (2017) · SSRN Electronic Journal

Explainable Artificial Intelligence (XAI)Ethics and Social Impacts of AI

Cited by 457

Reinforcement learning and episodic memory in humans and animals: an integrative framework

Gershman, S. J., & Daw, N. D. (2017) · Annual Review of Psychology

Reinforcement Learning in RoboticsMemory and Neural Mechanisms

Cited by 446

Context, learning, and extinction

Gershman, S. J., Blei, D. M., & Niv, Y. (2010) · Psychological Review

Memory and Neural MechanismsNeural and Behavioral Psychology Studies

Cited by 386

Reinforcement Learning in Multidimensional Environments Relies on Attention Mechanisms

Niv, Y., Daniel, R., Geana, A., Gershman, S. J., Leong, Y. C., Radulescu, A., & Wilson, R. C. (2015) · The Journal of Neuroscience

Neural and Behavioral Psychology StudiesReinforcement Learning in Robotics

Cited by 362

Learning latent structure: carving nature at its joints

Gershman, S. J., & Niv, Y. (2010) · Current Opinion in Neurobiology

Reinforcement Learning in RoboticsNeural and Behavioral Psychology Studies

Cited by 326

Toward a universal decoder of linguistic meaning from brain activation

Pereira, F., Lou, B., Pritchett, B., Ritter, S., Gershman, S. J., Kanwisher, N., Botvinick, M., & Fedorenko, E. (2018) · Nature Communications

Neurobiology of Language and BilingualismReading and Literacy Development

Cited by 324

Deconstructing the human algorithms for exploration

Gershman, S. J. (2018) · Cognition

Reinforcement Learning in RoboticsDecision-Making and Behavioral Economics

Cited by 267

Believing in dopamine

Gershman, S. J., & Uchida, N. (2019) · Nature Reviews Neuroscience

Neurotransmitter Receptor Influence on BehaviorNeural and Behavioral Psychology Studies

Cited by 236

Retrospective revaluation in sequential decision making: a tale of two systems

Gershman, S. J., Markman, A. B., & Otto, A. R. (2014) · Journal of Experimental Psychology General

Neural and Behavioral Psychology StudiesDecision-Making and Behavioral Economics

Cited by 217

When Does Model-Based Control Pay Off?

Kool, W., Cushman, F. A., & Gershman, S. J. (2016) · PLOS Computational Biology

Neural and Behavioral Psychology StudiesDecision-Making and Behavioral Economics

Cited by 211

Interplay of approximate planning strategies

Huys, Q. J. M., Lally, N., Faulkner, P., Eshel, N., Seifritz, E., Gershman, S. J., Dayan, P., & Roiser, J. P. (2015) · Proceedings of the National Academy of Sciences

Decision-Making and Behavioral EconomicsAI-based Problem Solving and Planning

Cited by 207

Dopamine reward prediction errors reflect hidden-state inference across time

Starkweather, C. K., Babayan, B. M., Uchida, N., & Gershman, S. J. (2017) · Nature Neuroscience

Neurotransmitter Receptor Influence on BehaviorNeural and Behavioral Psychology Studies

Cited by 206

The successor representation: Its computational logic and neural substrates

Gershman, S. J. (2018) · The Journal of Neuroscience

Reinforcement Learning in RoboticsMemory and Neural Mechanisms

Cited by 191

Structured Event Memory: A neuro-symbolic model of event cognition.

Franklin, N. T., Norman, K. A., Ranganath, C., Zacks, J. M., & Gershman, S. J. (2020) · Psychological Review

Memory Processes and InfluencesMemory and Neural Mechanisms

Cited by 177

The computational nature of memory modification

Gershman, S. J., Monfils, M.-H., Norman, K. A., & Niv, Y. (2017) · eLife

Memory and Neural MechanismsMemory Processes and Influences

Cited by 172

Resource-rational decision making

Bhui, R., Lai, L., & Gershman, S. J. (2021) · Current Opinion in Behavioral Sciences

Decision-Making and Behavioral EconomicsNeural and Behavioral Psychology Studies

Cited by 168

Hippocampal remapping as hidden state inference

Sanders, H., Wilson, M. A., & Gershman, S. J. (2020) · eLife

Memory and Neural MechanismsNeural dynamics and brain function

Cited by 163

Gradual extinction prevents the return of fear: implications for the discovery of state

Gershman, S. J., Jones, C. E., Norman, K. A., Monfils, M.-H., & Niv, Y. (2013) · Frontiers in Behavioral Neuroscience

Memory and Neural MechanismsMemory Processes and Influences

Cited by 160

Discovering latent causes in reinforcement learning

Gershman, S. J., Norman, K. A., & Niv, Y. (2015) · Current Opinion in Behavioral Sciences

Reinforcement Learning in RoboticsBayesian Modeling and Causal Inference

Cited by 151

Exploring a latent cause theory of classical conditioning

Gershman, S. J., & Niv, Y. (2012) · Learning & Behavior

Memory and Neural MechanismsBayesian Modeling and Causal Inference

Cited by 149