Models of value and choice.
暂无分享,去创建一个
[1] P. Dayan,et al. Model-based influences on humans’ choices and striatal prediction errors , 2011, Neuron.
[2] Colin Camerer,et al. Pavlovian Processes in Consumer Choice: The Physical Presence of a Good Increases Willingness-to-Pay , 2010 .
[3] P. Dayan,et al. States versus Rewards: Dissociable Neural Prediction Error Signals Underlying Model-Based and Model-Free Reinforcement Learning , 2010, Neuron.
[4] H. Varian. Computer Mediated Transactions , 2010 .
[5] Sara E. Morrison,et al. Re-valuing the amygdala , 2010, Current Opinion in Neurobiology.
[6] S. Kennerley,et al. Heterogeneous reward signals in prefrontal cortex , 2010, Current Opinion in Neurobiology.
[7] Matthijs A. A. van der Meer,et al. Hippocampal Replay Is Not a Simple Function of Experience , 2010, Neuron.
[8] B. Balleine,et al. Human and Rodent Homologies in Action Control: Corticostriatal Determinants of Goal-Directed and Habitual Action , 2010, Neuropsychopharmacology.
[9] P. Dayan,et al. Opponency Revisited: Competition and Cooperation Between Dopamine and Serotonin , 2010, Neuropsychopharmacology.
[10] Peter Dayan,et al. Values and Actions in Aversion , 2009 .
[11] P. Dayan,et al. A Bayesian formulation of behavioral control , 2009, Cognition.
[12] R. Hertwig,et al. The description–experience gap in risky choice , 2009, Trends in Cognitive Sciences.
[13] Emanuel Todorov,et al. Efficient computation of optimal actions , 2009, Proceedings of the National Academy of Sciences.
[14] P. Dayan,et al. Serotonin in affective control. , 2009, Annual review of neuroscience.
[15] B. Balleine,et al. A specific role for posterior dorsolateral striatum in human habit learning , 2009, The European journal of neuroscience.
[16] Y. Niv. Reinforcement learning in the brain , 2009 .
[17] J. W. Aldridge,et al. Dissecting components of reward: 'liking', 'wanting', and learning. , 2009, Current opinion in pharmacology.
[18] Richard L. Lewis,et al. Where Do Rewards Come From , 2009 .
[19] P. Dayan,et al. Decision theory, reinforcement learning, and the brain , 2008, Cognitive, affective & behavioral neuroscience.
[20] S. Peciña,et al. Opioid reward ‘liking’ and ‘wanting’ in the nucleus accumbens , 2008, Physiology & Behavior.
[21] K. Berridge,et al. Mesolimbic Dopamine in Desire and Dread: Enabling Motivation to Be Generated by Localized Glutamate Disruptions in Nucleus Accumbens , 2008, The Journal of Neuroscience.
[22] N. Daw,et al. Striatal Activity Underlies Novelty-Based Choice in Humans , 2008, Neuron.
[23] Peter Dayan,et al. Serotonin, Inhibition, and Negative Mood , 2007, PLoS Comput. Biol..
[24] Y. Smith,et al. Striatal and extrastriatal dopamine in the basal ganglia: An overview of its anatomical organization in normal and Parkinsonian brains , 2008, Movement disorders : official journal of the Movement Disorder Society.
[25] Peter Dayan,et al. The role of value systems in decision making. , 2008 .
[26] J. O'Doherty,et al. Lights, Camembert, Action! The Role of Human Orbitofrontal Cortex in Encoding Stimuli, Rewards, and Choices , 2007, Annals of the New York Academy of Sciences.
[27] C. Padoa-Schioppa. Orbitofrontal Cortex and the Computation of Economic Value , 2007, Annals of the New York Academy of Sciences.
[28] M. Roesch,et al. Dopamine neurons encode the better option in rats deciding between differently delayed or sized rewards , 2007, Nature Neuroscience.
[29] Thomas E. Hazy,et al. Towards an executive without a homunculus: computational models of the prefrontal cortex/basal ganglia system , 2007, Philosophical Transactions of the Royal Society B: Biological Sciences.
[30] A. Dickinson,et al. Western Scrub-Jays Anticipate Future Needs Independently of Their Current Motivational State , 2007, Current Biology.
[31] Vivian V. Valentin,et al. Determining the Neural Substrates of Goal-Directed Learning in the Human Brain , 2007, The Journal of Neuroscience.
[32] Pierre-Yves Oudeyer,et al. Intrinsic Motivation Systems for Autonomous Mental Development , 2007, IEEE Transactions on Evolutionary Computation.
[33] P. Dayan,et al. Hippocampal contributions to control: a normative perspective , 2007 .
[34] D. Kahneman,et al. Frames and brains: elicitation and control of response tendencies , 2007, Trends in Cognitive Sciences.
[35] P. Dayan,et al. Tonic dopamine: opportunity costs and the control of response vigor , 2007, Psychopharmacology.
[36] K. Berridge. The debate over dopamine’s role in reward: the case for incentive salience , 2007, Psychopharmacology.
[37] Peter Dayan,et al. Non-commercial Research and Educational Use including without Limitation Use in Instruction at Your Institution, Sending It to Specific Colleagues That You Know, and Providing a Copy to Your Institution's Administrator. All Other Uses, Reproduction and Distribution, including without Limitation Comm , 2022 .
[38] Jonathan D. Cohen,et al. The physics of optimal decision making: a formal analysis of models of performance in two-alternative forced-choice tasks. , 2006, Psychological review.
[39] D. Kumaran,et al. Frames, Biases, and Rational Decision-Making in the Human Brain , 2006, Science.
[40] E. Vaadia,et al. Midbrain dopamine neurons encode decisions for future action , 2006, Nature Neuroscience.
[41] M. Frank,et al. Anatomy of a decision: striato-orbitofrontal interactions in reinforcement learning, decision making, and reversal. , 2006, Psychological review.
[42] David J. Foster,et al. Reverse replay of behavioural sequences in hippocampal place cells during the awake state , 2006, Nature.
[43] B. Balleine. Neural bases of food-seeking: Affect, arousal and reward in corticostriatolimbic circuits , 2005, Physiology & Behavior.
[44] K. Berridge,et al. Hedonic Hot Spot in Nucleus Accumbens Shell: Where Do μ-Opioids Cause Increased Hedonic Impact of Sweetness? , 2005, The Journal of Neuroscience.
[45] P. Dayan,et al. Uncertainty-based competition between prefrontal and dorsolateral striatal systems for behavioral control , 2005, Nature Neuroscience.
[46] K. Doya,et al. Representation of Action-Specific Reward Values in the Striatum , 2005, Science.
[47] Richard S. Sutton,et al. Learning to predict by the methods of temporal differences , 1988, Machine Learning.
[48] Michael J. Frank,et al. By Carrot or by Stick: Cognitive Reinforcement Learning in Parkinsonism , 2004, Science.
[49] J. O'Doherty,et al. Reward representations and reward-related learning in the human brain: insights from neuroimaging , 2004, Current Opinion in Neurobiology.
[50] Nuttapong Chentanez,et al. Intrinsically Motivated Reinforcement Learning , 2004, NIPS.
[51] R. Hertwig,et al. Decisions from Experience and the Effect of Rare Events in Risky Choice , 2004, Psychological science.
[52] K. Berridge. Motivation concepts in behavioral neuroscience , 2004, Physiology & Behavior.
[53] E. Weber,et al. Predicting Risk-Sensitivity in Humans and Lower Animals: Risk as Variance or Coefficient of Variation , 2004, Psychological review.
[54] P. Holland. Relations between Pavlovian-instrumental transfer and reinforcer devaluation. , 2004, Journal of experimental psychology. Animal behavior processes.
[55] Nuttapong Chentanez,et al. Intrinsically Motivated Learning of Hierarchical Collections of Skills , 2004 .
[56] D. Kahneman. A perspective on judgment and choice: mapping bounded rationality. , 2003, The American psychologist.
[57] S. Killcross,et al. Coordination of actions and habits in the medial prefrontal cortex of rats. , 2003, Cerebral cortex.
[58] W. Schultz. Getting Formal with Dopamine and Reward , 2002, Neuron.
[59] K. Berridge,et al. Positive and Negative Motivation in Nucleus Accumbens Shell: Bivalent Rostrocaudal Gradients for GABA-Elicited Eating, Taste “Liking”/“Disliking” Reactions, Place Preference/Avoidance, and Fear , 2002, The Journal of Neuroscience.
[60] H. Pashler. STEVENS' HANDBOOK OF EXPERIMENTAL PSYCHOLOGY , 2002 .
[61] B. Balleine,et al. The Role of Learning in the Operation of Motivational Systems , 2002 .
[62] B. Everitt,et al. Emotion and motivation: the role of the amygdala, ventral striatum, and prefrontal cortex , 2002, Neuroscience & Biobehavioral Reviews.
[63] James L. McClelland,et al. The time course of perceptual choice: the leaky, competing accumulator model. , 2001, Psychological review.
[64] K. Berridge,et al. Fear and Feeding in the Nucleus Accumbens Shell: Rostrocaudal Segregation of GABA-Elicited Defensive Behavior Versus Eating Behavior , 2001, The Journal of Neuroscience.
[65] W. Schultz,et al. A neural network model with dopamine-like reinforcement signal that learns a spatial delayed response task , 1999, Neuroscience.
[66] Stuart J. Russell,et al. Bayesian Q-Learning , 1998, AAAI/IAAI.
[67] M. Corballis,et al. Mental time travel and the evolution of the human mind. , 1997, Genetic, social, and general psychology monographs.
[68] P. Dayan,et al. A framework for mesencephalic dopamine systems based on predictive Hebbian learning , 1996, The Journal of neuroscience : the official journal of the Society for Neuroscience.
[69] Ben J. A. Kröse,et al. Learning from delayed rewards , 1995, Robotics Auton. Syst..
[70] A. Barto. Adaptive Critics and the Basal Ganglia , 1995 .
[71] G. E. Alexander,et al. Functional architecture of basal ganglia circuits: neural substrates of parallel processing , 1990, Trends in Neurosciences.
[72] Richard S. Sutton,et al. Integrated Architectures for Learning, Planning, and Reacting Based on Approximating Dynamic Programming , 1990, ML.
[73] A. Tversky,et al. Anomalies: Preference Reversals , 1990 .
[74] Bernard Widrow,et al. Adaptive switching circuits , 1988 .
[75] D. Blanchard,et al. Ethoexperimental approaches to the biology of emotion. , 1988, Annual review of psychology.
[76] W. Hershberger. An approach through the looking-glass , 1986 .
[77] Richard S. Sutton,et al. Neuronlike adaptive elements that can solve difficult learning control problems , 1983, IEEE Transactions on Systems, Man, and Cybernetics.
[78] R. Rescorla,et al. A theory of Pavlovian conditioning : Variations in the effectiveness of reinforcement and nonreinforcement , 1972 .
[79] R. Bolles. Species-specific defense reactions and avoidance learning. , 1970 .
[80] D. R. Williams,et al. Auto-maintenance in the pigeon: sustained pecking despite contingent non-reinforcement. , 1969, Journal of the experimental analysis of behavior.
[81] Arthur L. Samuel,et al. Some Studies in Machine Learning Using the Game of Checkers , 1967, IBM J. Res. Dev..
[82] E. Tolman. There is more than one kind of learning. , 1949, Psychological review.