Decoy Effect and Violation of Betweenness in Risky Decision Making: A Resource-Rational Mechanistic Account
暂无分享,去创建一个
Ardavan Salehi Nobandegani | Thomas R. Shultz | Kevin da Silva Castanheira | A. Ross Otto | T. Shultz | A. R. Otto | A. S. Nobandegani
[1] Ardavan Salehi Nobandegani,et al. A Resource-Rational Process-Level Account of the St. Petersburg Paradox , 2020, CogSci.
[2] Falk Lieder,et al. Resource-rational analysis: Understanding human cognition as the optimal use of limited computational resources , 2019, Behavioral and Brain Sciences.
[3] Ardavan Salehi Nobandegani,et al. On Robustness: An Undervalued Dimension of Human Rationality , 2019, CogSci.
[4] Ardavan Salehi Nobandegani,et al. Sample-Based Variant of Expected Utility Explains Effects of Time Pressure and Individual Differences in Processing Speed on Risk Preferences , 2019, CogSci.
[5] Ardavan Salehi Nobandegani,et al. A Resource-Rational Mechanistic Approach to One-shot Non-cooperative Games: The Case of Prisoner's Dilemma , 2019, CogSci.
[6] Noah D. Goodman,et al. Empirical evidence for resource-rational anchoring and adjustment , 2017, Psychonomic Bulletin & Review.
[7] Ardavan Salehi Nobandegani,et al. Over-representation of Extreme Events in Decision-Making: A Rational Metacognitive Account , 2018, CogSci.
[8] Jörg Rieskamp,et al. Attraction Effect in Risky Choice Can Be Explained by Subjective Distance Between Choice Alternatives , 2017, Scientific Reports.
[9] Joshua B. Tenenbaum,et al. Building machines that learn and think like people , 2016, Behavioral and Brain Sciences.
[10] R. Hertwig. Decisions from Experience , 2015 .
[11] Samuel J. Gershman,et al. Computational rationality: A converging paradigm for intelligence in brains, minds, and machines , 2015, Science.
[12] Thomas L. Griffiths,et al. Rational Use of Cognitive Resources: Levels of Analysis Between the Computational and the Algorithmic , 2015, Top. Cogn. Sci..
[13] S. Denison,et al. Probabilistic models, learning algorithms, and response variability: sampling in cognitive development , 2014, Trends in Cognitive Sciences.
[14] Takao Noguchi,et al. In the attraction, compromise, and similarity effects, alternatives are repeatedly compared in pairs on single dimensions , 2014, Cognition.
[15] Thomas L. Griffiths,et al. One and Done? Optimal Decisions From Very Few Samples , 2014, Cogn. Sci..
[16] D. Read,et al. Prospect theory and the “forgotten” fourfold pattern of risk preferences , 2014 .
[17] J. Lygeros,et al. Decision Making I , 2014 .
[18] Jessica B. Hamrick,et al. Simulation as an engine of physical scene understanding , 2013, Proceedings of the National Academy of Sciences.
[19] Rémi Bardenet,et al. Monte Carlo Methods , 2013, Encyclopedia of Social Network Analysis and Mining. 2nd Ed..
[20] Robert H. Logie,et al. The Oxford Handbook of Cognitive Psychology , 2013 .
[21] Adam N. Sanborn,et al. Bridging Levels of Analysis for Probabilistic Models of Cognition , 2012 .
[22] Alireza Soltani,et al. A Range-Normalization Model of Context-Dependent Choice: A New Model and Evidence , 2012, PLoS Comput. Biol..
[23] Nick Chater,et al. Salience driven value integration explains decision biases and preference reversal , 2012, Proceedings of the National Academy of Sciences.
[24] Joshua B. Tenenbaum,et al. Multistability and Perceptual Inference , 2012, Neural Computation.
[25] Timothy J. Pleskac,et al. Decisions from experience: Why small samples? , 2010, Cognition.
[26] A. Tversky,et al. Prospect theory: an analysis of decision under risk — Source link , 2007 .
[27] Lynne M. Reder,et al. Metacognition in Strategy Selection , 2002 .
[28] Colin Camerer,et al. Violations of the betweenness axiom and nonlinearity in probability , 1994 .
[29] H. Vincent Poor,et al. An Introduction to Signal Detection and Estimation , 1994, Springer Texts in Electrical Engineering.
[30] Maxwell J. Roberts,et al. Strategy Selection and Metacognition , 1993 .
[31] Ola Svenson,et al. Theoretical and Empirical Approaches to Behavioral Decision Making and Their Relation to Time Constraints , 1993 .
[32] Ola Svenson,et al. Time pressure and stress in human judgment and decision making , 1993 .
[33] A. Tversky,et al. Advances in prospect theory: Cumulative representation of uncertainty , 1992 .
[34] D. H. Wedell,et al. Distinguishing Among Models of Contextually Induced Preference Reversals , 1991 .
[35] D. Prelec. A “Pseudo-endowment” effect, and its implications for some recent nonexpected utility models , 1990 .
[36] J. Geweke,et al. Bayesian Inference in Econometric Models Using Monte Carlo Integration , 1989 .
[37] I. Simonson,et al. Choice Based on Reasons: The Case of Attraction and Compromise Effects , 1989 .
[38] M. Machina. Choice under Uncertainty: Problems Solved and Unsolved , 1987 .
[39] J. Payne,et al. Adding Asymmetrically Dominated Alternatives: Violations of Regularity & the Similarity Hypothesis. , 1981 .
[40] P. Schoemaker,et al. Prospect theory's reflection hypothesis: A critical examination , 1980 .
[41] Larry D. Rosen,et al. An eye fixation analysis of multialternative choice , 1975, Memory & cognition.
[42] Daniel Kahneman,et al. Availability: A heuristic for judging frequency and probability , 1973 .
[43] D. Bernoulli. Exposition of a New Theory on the Measurement of Risk , 1954 .
[44] H. Markowitz. The Utility of Wealth , 1952, Journal of Political Economy.
[45] L. A. Goodman,et al. Social Choice and Individual Values , 1951 .
[46] J. Neumann,et al. Theory of games and economic behavior , 1945, 100 Years of Math Milestones.