New Results
Predictive representations can link model-based reinforcement learning to model-free mechanisms
Evan M. Russek, Ida Momennejad, Matthew M. Botvinick, Samuel J. Gershman, Nathaniel D. Daw
doi: https://doi.org/10.1101/083857
Evan M. Russek
1Center for Neural Science, New York University, New York, NY, United States of America
Ida Momennejad
2Princeton Neuroscience Institute and Department of Psychology, Princeton University, Princeton, NJ, United States of America
Matthew M. Botvinick
3Google DeepMind, London, United Kingdom
Samuel J. Gershman
4Department of Psychology and Center for Brain Science, Harvard University, Cambridge, MA, United States of America
Nathaniel D. Daw
2Princeton Neuroscience Institute and Department of Psychology, Princeton University, Princeton, NJ, United States of America
Article usage
Posted October 27, 2016.
Predictive representations can link model-based reinforcement learning to model-free mechanisms
Evan M. Russek, Ida Momennejad, Matthew M. Botvinick, Samuel J. Gershman, Nathaniel D. Daw
bioRxiv 083857; doi: https://doi.org/10.1101/083857
Subject Area
Subject Areas
- Biochemistry (11573)
- Bioengineering (8623)
- Bioinformatics (28874)
- Biophysics (14805)
- Cancer Biology (11944)
- Cell Biology (17170)
- Clinical Trials (138)
- Developmental Biology (9306)
- Ecology (14022)
- Epidemiology (2067)
- Evolutionary Biology (18129)
- Genetics (12148)
- Genomics (16619)
- Immunology (11709)
- Microbiology (27697)
- Molecular Biology (11392)
- Neuroscience (60106)
- Paleontology (447)
- Pathology (1849)
- Pharmacology and Toxicology (3184)
- Physiology (4878)
- Plant Biology (10279)
- Synthetic Biology (2849)
- Systems Biology (7291)
- Zoology (1619)