The roles of online and offline replay in planning
暂无分享,去创建一个
Peter Dayan | Raymond J. Dolan | Gaëlle Lièvre | Eran Eldar | P. Dayan | R. Dolan | Eran Eldar | Gaëlle Lièvre
[1] R. Jackendoff. What is a cognitive map? , 1979, Behavioral and Brain Sciences.
[2] Richard S. Sutton,et al. Dyna, an integrated architecture for learning, planning, and reacting , 1990, SGAR.
[3] Jing Peng,et al. Efficient Learning and Planning Within the Dyna Framework , 1993, Adapt. Behav..
[4] B. McNaughton,et al. Replay of Neuronal Firing Sequences in Rat Hippocampus During Sleep Following Spatial Experience , 1996, Science.
[5] K. Stanovich,et al. Heuristics and Biases: Individual Differences in Reasoning: Implications for the Rationality Debate? , 2002 .
[6] K. Stanovich,et al. Individual differences in reasoning: Implications for the rationality debate? , 2000, Behavioral and Brain Sciences.
[7] M. Wilson,et al. Temporally Structured Replay of Awake Hippocampal Ensemble Activity during Rapid Eye Movement Sleep , 2001, Neuron.
[8] Karl J. Friston,et al. Temporal Difference Models and Reward-Related Learning in the Human Brain , 2003, Neuron.
[9] Andrew W. Moore,et al. Prioritized sweeping: Reinforcement learning with less data and less time , 2004, Machine Learning.
[10] Andrew W. Moore,et al. Prioritized Sweeping: Reinforcement Learning with Less Data and Less Time , 1993, Machine Learning.
[11] T. Robbins,et al. Neural systems of reinforcement for drug addiction: from actions to habits to compulsion , 2005, Nature Neuroscience.
[12] P. Dayan,et al. Uncertainty-based competition between prefrontal and dorsolateral striatal systems for behavioral control , 2005, Nature Neuroscience.
[13] Richard S. Sutton,et al. Reinforcement Learning: An Introduction , 1998, IEEE Trans. Neural Networks.
[14] David J. Foster,et al. Reverse replay of behavioural sequences in hippocampal place cells during the awake state , 2006, Nature.
[15] Radford M. Neal. Pattern Recognition and Machine Learning , 2007, Technometrics.
[16] G. Buzsáki,et al. Forward and reverse hippocampal place-cell sequences during ripples , 2007, Nature Neuroscience.
[17] M. Wilson,et al. Coordinated memory replay in the visual cortex and hippocampus during sleep , 2007, Nature Neuroscience.
[18] P. Dayan,et al. States versus Rewards: Dissociable Neural Prediction Error Signals Underlying Model-Based and Model-Free Reinforcement Learning , 2010, Neuron.
[19] Matthijs A. A. van der Meer,et al. Hippocampal Replay Is Not a Simple Function of Experience , 2010, Neuron.
[20] Chih-Jen Lin,et al. LIBSVM: A library for support vector machines , 2011, TIST.
[21] Robert Oostenveld,et al. FieldTrip: Open Source Software for Advanced Analysis of MEG, EEG, and Invasive Electrophysiological Data , 2010, Comput. Intell. Neurosci..
[22] P. Dayan,et al. Model-based influences on humans’ choices and striatal prediction errors , 2011, Neuron.
[23] Peter Dayan,et al. Bonsai Trees in Your Head: How the Pavlovian System Sculpts Goal-Directed Choices by Pruning Decision Trees , 2012, PLoS Comput. Biol..
[24] M. Woolrich,et al. Mechanisms underlying cortical activity during value-guided choice , 2011, Nature Neuroscience.
[25] Brad E. Pfeiffer,et al. Hippocampal place cell sequences depict future paths to remembered goals , 2013, Nature.
[26] M. Crockett. Models of morality , 2013, Trends in Cognitive Sciences.
[27] Tandra Ghose,et al. Generalization between canonical and non-canonical views in object recognition. , 2013, Journal of vision.
[28] David A. Tovar,et al. Representational dynamics of object vision: the first 1000 ms. , 2013, Journal of vision.
[29] John K. Kruschke,et al. Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan , 2014 .
[30] R Core Team,et al. R: A language and environment for statistical computing. , 2014 .
[31] Radoslaw Martin Cichy,et al. Resolving human object recognition in space and time , 2014, Nature Neuroscience.
[32] N. McGlynn. Thinking fast and slow. , 2014, Australian veterinary journal.
[33] Matthijs A. A. van der Meer,et al. Internally generated sequences in learning and executing goal-directed behavior , 2014, Trends in Cognitive Sciences.
[34] A. Markman,et al. Journal of Experimental Psychology : General Retrospective Revaluation in Sequential Decision Making : A Tale of Two Systems , 2012 .
[35] Joel Z. Leibo,et al. The dynamics of invariant object recognition in the human visual system. , 2014, Journal of neurophysiology.
[36] D. Hassabis,et al. Hippocampal place cells construct reward related sequences through unexplored space , 2015, eLife.
[37] N. Daw,et al. Model-based learning protects against forming habits , 2015, Cognitive, Affective, & Behavioral Neuroscience.
[38] P. Dayan,et al. Temporal structure in associative retrieval , 2015, eLife.
[39] Zeb Kurth-Nelson,et al. Fast Sequences of Non-spatial State Representations in Humans , 2016, Neuron.
[40] Wouter Kool,et al. When Does Model-Based Control Pay Off? , 2016, PLoS Comput. Biol..
[41] Catherine A. Hartley,et al. From Creatures of Habit to Goal-Directed Learners , 2016, Psychological science.
[42] P. Dayan,et al. Striatal structure and function predict individual biases in learning to avoid pain , 2016, Proceedings of the National Academy of Sciences.
[43] Kimberly L. Stachenfeld,et al. The hippocampus as a predictive map , 2017, Nature Neuroscience.
[44] P. Dayan,et al. Single-Trial Inhibition of Anterior Cingulate Disrupts Model-based Reinforcement Learning in a Two-step Decision Task. , 2017 .
[45] Samuel Gershman,et al. Predictive representations can link model-based reinforcement learning to model-free mechanisms , 2017, bioRxiv.
[46] C. Barry,et al. Task Demands Predict a Dynamic Switch in the Content of Awake Hippocampal Replay , 2017, Neuron.
[47] Jiqiang Guo,et al. Stan: A Probabilistic Programming Language. , 2017, Journal of statistical software.
[48] T. Robbins,et al. A trans-diagnostic perspective on obsessive-compulsive disorder , 2017, Psychological Medicine.
[49] David J. Foster. Replay Comes of Age. , 2017, Annual review of neuroscience.
[50] M. Botvinick,et al. The hippocampus as a predictive map , 2016 .
[51] Marcelo G Mattar,et al. Prioritized memory access explains planning and hippocampal replay , 2017, Nature Neuroscience.
[52] Ida Momennejad,et al. Offline replay supports planning in human reinforcement learning , 2018, eLife.
[53] Alyssa A. Carey,et al. Reward revaluation biases hippocampal sequence content away from the preferred outcome , 2018, bioRxiv.
[54] Zeb Kurth-Nelson,et al. What Is a Cognitive Map? Organizing Knowledge for Flexible Behavior , 2018, Neuron.
[55] Zeb Kurth-Nelson,et al. Magnetoencephalography decoding reveals structural differences within integrative decision processes , 2018, Nature Human Behaviour.
[56] Benedek Kurdi,et al. Model-free and model-based learning processes in the updating of explicit and implicit evaluations , 2019, Proceedings of the National Academy of Sciences.
[57] Timothy E. J. Behrens,et al. Human Replay Spontaneously Reorganizes Experience , 2019, Cell.
[58] Todd A. Hare,et al. Model-free or muddled models in the two-stage task? , 2019 .
[59] Nicolas W. Schuck,et al. Sequential replay of nonspatial task states in the human hippocampus , 2018, Science.
[60] P. Dayan,et al. Anterior cingulate cortex represents action-state predictions and causally mediates model-based reinforcement learning in a two-step decision task , 2020, bioRxiv.