Overrepresentation of Extreme Events in Decision Making Reflects Rational Use of Cognitive Resources
暂无分享,去创建一个
[1] Ole Hagen,et al. Towards a Positive Theory of Preferences under Risk , 1979 .
[2] J. Geweke,et al. Bayesian Inference in Econometric Models Using Monte Carlo Integration , 1989 .
[3] J. Olesen,et al. Epidemiology of headache in a general population--a prevalence study. , 1991, Journal of clinical epidemiology.
[4] Elliot A. Ludvig,et al. The Role of Memory in Distinguishing Risky Decisions from Experience and Description , 2017, Quarterly journal of experimental psychology.
[5] J. Neumann,et al. Theory of games and economic behavior , 1945, 100 Years of Math Milestones.
[6] R. Hertwig,et al. The priority heuristic: making choices without trade-offs. , 2006, Psychological review.
[7] Trevor Hastie,et al. The Elements of Statistical Learning , 2001 .
[8] G. Gigerenzer. Simply Rational: Decision Making in the Real World , 2015 .
[9] Gerd Gigerenzer,et al. Homo Heuristicus: Why Biased Minds Make Better Inferences , 2009, Top. Cogn. Sci..
[10] A. Rangel,et al. Multialternative drift-diffusion model predicts the relationship between visual fixations and choice in value-based decisions , 2011, Proceedings of the National Academy of Sciences.
[11] E. Wagenmakers,et al. Hierarchical Bayesian parameter estimation for cumulative prospect theory , 2011, Journal of Mathematical Psychology.
[12] J. Hammersley,et al. Monte Carlo Methods , 1965 .
[13] M. Shadlen,et al. Decision Making and Sequential Sampling from Memory , 2016, Neuron.
[14] M. Allais. The Foundations of a Positive Theory of Choice Involving Risk and a Criticism of the Postulates and Axioms of the American School (1952) , 1979 .
[15] Ori Plonsky,et al. Reliance on small samples, the wavy recency effect, and similarity-based learning. , 2015, Psychological review.
[16] G. Mulder. The Concept and Measurement of Mental Effort , 1986 .
[17] Cleotilde Gonzalez,et al. Instance-based learning in dynamic decision making , 2003, Cogn. Sci..
[18] Man-Suk Oh,et al. Adaptive importance sampling in monte carlo integration , 1992 .
[19] Thomas L. Griffiths,et al. "Burn-in, bias, and the rationality of anchoring" , 2012, NIPS.
[20] L. Tierney,et al. Accurate Approximations for Posterior Moments and Marginal Densities , 1986 .
[21] John R. Anderson,et al. The Adaptive Character of Thought , 1990 .
[22] Hugh LaFollette,et al. International encyclopedia of ethics. , 2013 .
[23] Thomas L. Griffiths,et al. One and Done? Optimal Decisions From Very Few Samples , 2014, Cogn. Sci..
[24] James L McGaugh,et al. Amygdala Modulation of Memory Consolidation: Interaction with Other Brain Systems , 2002, Neurobiology of Learning and Memory.
[25] R. Hertwig,et al. Judgments of risk frequencies: tests of possible cognitive mechanisms. , 2005, Journal of experimental psychology. Learning, memory, and cognition.
[26] Aaron C. Courville,et al. Bayesian theories of conditioning in a changing world , 2006, Trends in Cognitive Sciences.
[27] Wolfgang Maass,et al. On the Computational Power of Winner-Take-All , 2000, Neural Computation.
[28] R. Hertwig,et al. How (in)variant are subjective representations of described and experienced risk and rewards? , 2016, Cognition.
[29] C. Sims. Implications of rational inattention , 2003 .
[30] Gerd Gigerenzer,et al. Why Heuristics Work , 2008, Perspectives on psychological science : a journal of the Association for Psychological Science.
[31] Thomas L. Griffiths,et al. Think again? The amount of mental simulation tracks uncertainty in the outcome , 2015, CogSci.
[32] C. Lebiere,et al. Applying Cognitive Architectures to Decision-Making: How Cognitive Theory and the Equivalence Measure Triumphed in the Technion Prediction Tournament , 2009 .
[33] Mel W. Khaw,et al. Normalization is a general neural mechanism for context-dependent decision making , 2013, Proceedings of the National Academy of Sciences.
[34] David Tolpin,et al. Selecting Computations: Theory and Applications , 2012, UAI.
[35] P. Corr. Reinforcement sensitivity theory and personality , 2004, Neuroscience & Biobehavioral Reviews.
[36] U. Hahn,et al. Perceptuo-motor, cognitive, and description-based decision-making seem equally good , 2013, Proceedings of the National Academy of Sciences.
[37] R. Hertwig,et al. The description–experience gap in risky choice , 2009, Trends in Cognitive Sciences.
[38] B. Fischhoff,et al. Judged frequency of lethal events , 1978 .
[39] Peter Dayan,et al. A Neural Substrate of Prediction and Reward , 1997, Science.
[40] C. Starmer. Developments in Non-expected Utility Theory: The Hunt for a Descriptive Theory of Choice under Risk , 2000 .
[41] Marcia L. Spetch,et al. Remembering the best and worst of times: Memories for extreme outcomes bias risky decisions , 2013, Psychonomic Bulletin & Review.
[42] D. Goldstein,et al. Word count: 3998 Corresponding author: , 2022 .
[43] T. Robbins,et al. Involvement of the amygdala in stimulus-reward associations: Interaction with the ventral striatum , 1989, Neuroscience.
[44] Robert Sugden,et al. Probability and juxtaposition effects: An experimental investigation of the common ratio effect , 1989 .
[45] Ido Erev,et al. Noisy retrieval models of over- and undersensitivity to rare events , 2015 .
[46] Neil Stewart,et al. A decision-by-sampling account of decision under risk , 2008 .
[47] Daniel Kahneman,et al. Availability: A heuristic for judging frequency and probability , 1973 .
[48] R. Hertwig,et al. Decisions from Experience and the Effect of Rare Events in Risky Choice , 2004, Psychological science.
[49] John R. Anderson,et al. Reflections of the Environment in Memory Form of the Memory Functions , 2022 .
[50] Y. Niv. Reinforcement learning in the brain , 2009 .
[51] R. Thaler,et al. Gambling with the house money and trying to break even: the effects of prior outcomes on risky choice , 1990 .
[52] Falk Lieder,et al. An automatic method for discovering rational heuristics for risky choice , 2017, CogSci.
[53] John Dickhaut,et al. A neuroeconomic theory of the decision process , 2009, Proceedings of the National Academy of Sciences.
[54] J. Pearce,et al. A model for Pavlovian learning: Variations in the effectiveness of conditioned but not of unconditioned stimuli. , 1980 .
[55] Thomas L. Griffiths,et al. Rational Use of Cognitive Resources: Levels of Analysis Between the Computational and the Algorithmic , 2015, Top. Cogn. Sci..
[56] Guillem R. Esber,et al. Surprise! Neural correlates of Pearce–Hall and Rescorla–Wagner coexist within the brain , 2012, The European journal of neuroscience.
[57] P. Berkes,et al. Statistically Optimal Perception and Learning: from Behavior to Neural Representations , 2022 .
[58] Ben R. Newell,et al. Modeling probability knowledge and choice in decisions from experience , 2014, CogSci.
[59] C. Summerfield,et al. Do humans make good decisions? , 2015, Trends in Cognitive Sciences.
[60] Thomas L. Griffiths,et al. When to use which heuristic: A rational solution to the strategy selection problem , 2015, CogSci.
[61] Marcia L. Spetch,et al. Extreme outcomes sway risky decisions from experience , 2014 .
[62] Thorsten Pachur,et al. How do people judge risks: availability heuristic, affect heuristic, or both? , 2012, Journal of experimental psychology. Applied.
[63] G. Marcus. Kluge : the haphazard evolution of the human mind , 2009 .
[64] Cleotilde Gonzalez,et al. Instance‐based Learning: A General Model of Repeated Binary Choice , 2012 .
[65] Neil Stewart. EPS Prize Lecture: Decision by sampling: The role of the decision environment in risky choice , 2009, Quarterly journal of experimental psychology.
[66] S. Denison,et al. Rational variability in children’s causal inferences: The Sampling Hypothesis , 2013, Cognition.
[67] Timothy J. Pleskac,et al. Ecologically rational choice and the structure of the environment. , 2014, Journal of experimental psychology. General.
[68] Robert Sugden,et al. The Importance of What Might Have Been , 1984 .
[69] R. Sugden,et al. Regret Theory: An alternative theory of rational choice under uncertainty Review of Economic Studies , 1982 .
[70] N. Chater,et al. Précis of Bayesian Rationality: The Probabilistic Approach to Human Reasoning , 2009, Behavioral and Brain Sciences.
[71] A. Denis. Rationality , 2012, Encyclopedia of Evolutionary Psychological Science.
[72] J. Rieskamp. The probabilistic nature of preferential choice. , 2008, Journal of experimental psychology. Learning, memory, and cognition.
[73] Varun Dutt,et al. Instance-based learning: integrating sampling and repeated decisions from experience. , 2011, Psychological review.
[74] F. Attneave. Psychological probability as a function of experienced frequency. , 1953, Journal of experimental psychology.
[75] A. Tversky,et al. Advances in prospect theory: Cumulative representation of uncertainty , 1992 .
[76] P. Glimcher,et al. Reward Value-Based Gain Control: Divisive Normalization in Parietal Cortex , 2011, The Journal of Neuroscience.
[77] Thomas L. Griffiths,et al. Neural Implementation of Hierarchical Bayesian Inference by Importance Sampling , 2009, NIPS.
[78] Alvin E. Roth,et al. A choice prediction competition: Choices from experience and from description , 2010 .
[79] M. Lengyel,et al. On the role of time in perceptual decision making , 2015, 1502.03135.
[80] A. Shleifer,et al. Salience Theory of Choice Under Risk , 2010 .
[81] C. Hobson,et al. Stressful Life Events: A Revision and Update of the Social Readjustment Rating Scale , 1998 .
[82] Alexandre Pouget,et al. Optimal policy for value-based decision-making , 2016, Nature Communications.
[83] David E. Bell,et al. Disappointment in Decision Making Under Uncertainty , 1985, Oper. Res..
[84] Alexander J. Rothman,et al. Absolute and Relative Biases in Estimations of Personal Risk , 1996 .
[85] P. Todd,et al. Ecological Rationality: Intelligence in the World , 2012 .
[86] S. Lazic,et al. Introducing Monte Carlo Methods with R , 2012 .
[87] Robert Sugden,et al. Disappointment and Dynamic Consistency in Choice under Uncertainty , 1986 .
[88] Elizabeth F. Loftus,et al. Memory for traumatic events , 1987 .
[89] Brian Knutson,et al. Reward-Motivated Learning: Mesolimbic Activation Precedes Memory Formation , 2006, Neuron.
[90] Richard Gonzalez,et al. On the Shape of the Probability Weighting Function , 1999, Cognitive Psychology.
[91] C. Hobson,et al. National Norms and Life-Event Frequencies for the Revised Social Readjustment Rating Scale , 2001 .
[92] J. Tenenbaum,et al. Optimal Predictions in Everyday Cognition , 2006, Psychological science.
[93] I. Erev,et al. Small feedback‐based decisions and their limited correspondence to description‐based decisions , 2003 .
[94] Hang Zhang,et al. Ubiquitous Log Odds: A Common Representation of Probability and Frequency Distortion in Perception, Action, and Cognition , 2012, Front. Neurosci..
[95] S. Sutherland. Irrationality: The Enemy Within , 1992 .
[96] Eric J. Johnson,et al. Aspects of Endowment: A Query Theory of Value Construction , 2007, Journal of experimental psychology. Learning, memory, and cognition.
[97] Adam N Sanborn,et al. Exemplar models as a mechanism for performing Bayesian inference , 2010, Psychonomic bulletin & review.
[98] A. Tversky,et al. Judgment under Uncertainty: Heuristics and Biases , 1974, Science.
[99] R. Herrnstein,et al. Maximizing and matching on concurrent ratio schedules. , 1975, Journal of the experimental analysis of behavior.
[100] Gordon D. A. Brown,et al. Decision by sampling , 2006, Cognitive Psychology.
[101] R. Zeckhauser,et al. Overreaction to Fearsome Risks , 2008 .
[102] Adam N. Sanborn,et al. Bridging Levels of Analysis for Probabilistic Models of Cognition , 2012 .
[103] A. Rangel,et al. Visual fixations and the computation and comparison of value in simple choice. , 2010, Nature neuroscience.
[104] Nir Vulkan. An Economist's Perspective on Probability Matching , 2000 .
[105] H. Simon,et al. Rational choice and the structure of the environment. , 1956, Psychological review.
[106] T. Griffiths,et al. Strategy Selection as Rational Metareasoning , 2017, Psychological review.
[107] A. Tversky,et al. Prospect theory: an analysis of decision under risk — Source link , 2007 .
[108] R. Weale. Vision. A Computational Investigation Into the Human Representation and Processing of Visual Information. David Marr , 1983 .
[109] E. Rowland. Theory of Games and Economic Behavior , 1946, Nature.
[110] Thomas L. Griffiths,et al. The high availability of extreme events serves resource-rational decision-making , 2014, CogSci.
[111] Richard J. Tunney,et al. Value representations by rank order in a distributed network of varying context dependency , 2013, Brain and Cognition.
[112] B. Newell. Judgment Under Uncertainty , 2013 .
[113] Eric J. Johnson,et al. Behavioral decision research: A constructive processing perspective. , 1992 .
[114] M. Allais. Le comportement de l'homme rationnel devant le risque : critique des postulats et axiomes de l'ecole americaine , 1953 .
[115] Neil Stewart,et al. On the Origin of Utility, Weighting, and Discounting Functions: How They Get Their Shapes and How to Change Their Shapes , 2015, Manag. Sci..
[116] S. Cabib,et al. Positive and negative emotional arousal increases duration of memory traces: common and independent mechanisms , 2011, Front. Behav. Neurosci..
[117] A. Tversky. Intransitivity of preferences. , 1969 .
[118] P. Slovic,et al. Reversals of preference between bids and choices in gambling decisions. , 1971 .
[119] Richard J. Herrnstein,et al. MAXIMIZING AND MATCHING ON CONCURRENT RATIO SCHEDULES1 , 1975 .
[120] H. Stott. Cumulative prospect theory's functional menagerie , 2006 .
[121] Nick Chater,et al. Economic irrationality is optimal during noisy decision making , 2016, Proceedings of the National Academy of Sciences.
[122] J. Quiggin. A theory of anticipated utility , 1982 .
[123] Sudeep Bhatia,et al. Associations and the accumulation of preference. , 2013, Psychological review.
[124] R. Thaler,et al. Deal or No Deal? Decision Making under Risk in a Large-Payoff Game Show , 2008 .
[125] Wolfgang Maass,et al. Bayesian Computation Emerges in Generic Cortical Microcircuits through Spike-Timing-Dependent Plasticity , 2013, PLoS Comput. Biol..
[126] Wolfgang Maass,et al. Neural Dynamics as Sampling: A Model for Stochastic Computation in Recurrent Networks of Spiking Neurons , 2011, PLoS Comput. Biol..
[127] J. D. McGaugh. The amygdala modulates the consolidation of memories of emotionally arousing experiences. , 2004, Annual review of neuroscience.
[128] Y. Loewenstein,et al. The role of first impression in operant learning. , 2013, Journal of experimental psychology. General.
[129] Ben R. Newell,et al. The Exemplar Confusion Model: An Account of Biased Probability Estimates in Decisions from Description , 2015, CogSci.
[130] Leslie Pack Kaelbling,et al. Bayesian Optimization with Exponential Convergence , 2015, NIPS.
[131] W. Edwards. Subjective probabilities inferred from decisions. , 1962, Psychological review.