Computational evidence for hierarchically structured reinforcement learning in humans

Resource-rational analysis: understanding human cognition as the optimal use of limited computational resources

(2019) Falk Lieder et al.   BEHAVIORAL AND BRAIN SCIENCES

Reinforcement learning: bringing together computation and cognition

(2019) Anne Gabrielle Eva Collins   Current Opinion in Behavioral Sciences

Doing more with less: meta-reasoning and meta-learning in humans and machines

(2019) Thomas L Griffiths et al.   Current Opinion in Behavioral Sciences

Prefrontal cortex as a meta-reinforcement learning system

(2018) Jane X. Wang et al.   NATURE NEUROSCIENCE

Comparing continual task learning in minds and machines

(2018) Timo Flesch et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

On the necessity of abstraction

(2018) George Konidaris   Current Opinion in Behavioral Sciences

Dynamic Interaction between Reinforcement Learning and Attention in Multidimensional Environments

(2017) Yuan Chang Leong et al.   NEURON

On the Blessing of Abstraction

(2017) Samuel J. Gershman   QUARTERLY JOURNAL OF EXPERIMENTAL PSYCHOLOGY

The Importance of Falsification in Computational Cognitive Modeling

(2017) Stefano Palminteri et al.   TRENDS IN COGNITIVE SCIENCES

Feature-based learning improves adaptability without compromising precision

(2017) Shiva Farashahi et al.   Nature Communications

Building machines that learn and think like people

(2016) Brenden M. Lake et al.   BEHAVIORAL AND BRAIN SCIENCES

The MAGE protein family and cancer

(2015) Jenny L Weon et al.   CURRENT OPINION IN CELL BIOLOGY

Reinforcement Learning in Multidimensional Environments Relies on Attention Mechanisms

(2015) Y. Niv et al.   JOURNAL OF NEUROSCIENCE

Hierarchical Error Representation: A Computational Model of Anterior Cingulate and Dorsolateral Prefrontal Cortex

(2015) William H. Alexander et al.   NEURAL COMPUTATION

Human EEG Uncovers Latent Generalizable Rule Structure during Learning

(2014) A. G. E. Collins et al.   JOURNAL OF NEUROSCIENCE

Foundations of human reasoning in the prefrontal cortex

(2014) M. Donoso et al.   SCIENCE

Optimal Behavioral Hierarchy

(2014) Alec Solway et al.   PLoS Computational Biology

Hierarchical Learning Induces Two Simultaneous, But Separable, Prediction Errors in Human Basal Ganglia

(2013) C. Diuk et al.   JOURNAL OF NEUROSCIENCE

The nature and transfer of cognitive skills.

(2013) Niels A. Taatgen   PSYCHOLOGICAL REVIEW

Cognitive control over learning: Creating, clustering, and generalizing task-set structure.

(2013) Anne G. E. Collins et al.   PSYCHOLOGICAL REVIEW

Approximate Bayesian Computation

(2013) Mikael Sunnåker et al.   PLoS Computational Biology

Neural Basis of Reinforcement Learning and Decision Making

(2012) Daeyeol Lee et al.   Annual Review of Neuroscience

Hierarchical reinforcement learning and decision making

(2012) Matthew Michael Botvinick   CURRENT OPINION IN NEUROBIOLOGY

Updating dopamine reward signals

(2012) Wolfram Schultz   CURRENT OPINION IN NEUROBIOLOGY

Inferring Relevance in a Changing World

(2012) Robert C. Wilson et al.   Frontiers in Human Neuroscience

Transient stimulation of distinct subpopulations of striatal neurons mimics changes in action value

(2012) Lung-Hao Tai et al.   NATURE NEUROSCIENCE

Reasoning, Learning, and Creativity: Frontal Lobe Function and Human Decision-Making

(2012) Anne Collins et al.   PLOS BIOLOGY

Mechanisms of Hierarchical Reinforcement Learning in Corticostriatal Circuits 1: Computational Analysis

(2011) Michael J. Frank et al.   CEREBRAL CORTEX

Mechanisms of Hierarchical Reinforcement Learning in Cortico-Striatal Circuits 2: Evidence from fMRI

(2011) D. Badre et al.   CEREBRAL CORTEX

Dopamine-Mediated Reinforcement Learning Signals in the Striatum and Ventromedial Prefrontal Cortex Underlie Value-Based Choices

(2011) G. Jocham et al.   JOURNAL OF NEUROSCIENCE

A Neural Signature of Hierarchical Reinforcement Learning

(2011) José J.F. Ribas-Fernandes et al.   NEURON

How to Grow a Mind: Statistics, Structure, and Abstraction

(2011) J. B. Tenenbaum et al.   SCIENCE

How cognitive modeling can benefit from hierarchical Bayesian models

(2010) Michael D. Lee   JOURNAL OF MATHEMATICAL PSYCHOLOGY

Is the rostro-caudal axis of the frontal lobe hierarchical?

(2009) David Badre et al.   NATURE REVIEWS NEUROSCIENCE

Cognitive control, hierarchy, and the rostro–caudal organization of the frontal lobes

(2008) David Badre   TRENDS IN COGNITIVE SCIENCES