Rational Use of Cognitive Resources: Levels of Analysis Between the Computational and the Algorithmic
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[1] A. Turing. On Computable Numbers, with an Application to the Entscheidungsproblem. , 1937 .
[2] H. Simon,et al. A Behavioral Model of Rational Choice , 1955 .
[3] A. Tversky,et al. Judgment under Uncertainty: Heuristics and Biases , 1974, Science.
[4] Richard J. Herrnstein,et al. MAXIMIZING AND MATCHING ON CONCURRENT RATIO SCHEDULES1 , 1975 .
[5] Tomaso Poggio,et al. From Understanding Computation to Understanding Neural Circuitry , 1976 .
[6] John R. Anderson. Arguments concerning representations for mental imagery. , 1978 .
[7] Allen Newell,et al. The Knowledge Level , 1989, Artif. Intell..
[8] M. Arbib. Levels of modeling of mechanisms of visually guided behavior , 1987, Behavioral and Brain Sciences.
[9] Allen Newell,et al. SOAR: An Architecture for General Intelligence , 1987, Artif. Intell..
[10] Eric Horvitz,et al. Reasoning under Varying and Uncertain Resource Constraints , 1988, AAAI.
[11] John R. Anderson. The Adaptive Character of Thought , 1990 .
[12] John R. Anderson,et al. The Adaptive Nature of Human Categorization , 1991 .
[13] Stuart J. Russell,et al. Do the right thing - studies in limited rationality , 1991 .
[14] Stuart J. Russell,et al. Principles of Metareasoning , 1989, Artif. Intell..
[15] Stuart J. Russell. Rationality and Intelligence , 1995, IJCAI.
[16] D E Kieras,et al. A computational theory of executive cognitive processes and multiple-task performance: Part 1. Basic mechanisms. , 1997, Psychological review.
[17] N. Chater,et al. Ten years of the rational analysis of cognition , 1999, Trends in Cognitive Sciences.
[18] P. Todd,et al. Simple Heuristics That Make Us Smart , 1999 .
[19] Refractor. Vision , 2000, The Lancet.
[20] Charles Wallis,et al. Computation and cognition , 2003, J. Exp. Theor. Artif. Intell..
[21] John R Anderson,et al. An integrated theory of the mind. , 2004, Psychological review.
[22] Thomas L. Griffiths,et al. A more rational model of categorization , 2006 .
[23] Naomi H. Feldman,et al. Performing Bayesian Inference with Exemplar Models , 2008 .
[24] Richard L. Lewis,et al. Rational adaptation under task and processing constraints: implications for testing theories of cognition and action. , 2009, Psychological review.
[25] Thomas L. Griffiths,et al. Neural Implementation of Hierarchical Bayesian Inference by Importance Sampling , 2009, NIPS.
[26] Wayne D. Gray,et al. Topics in Cognitive Science , 2009 .
[27] Adam N Sanborn,et al. Exemplar models as a mechanism for performing Bayesian inference , 2010, Psychonomic bulletin & review.
[28] J. Tenenbaum,et al. Probabilistic models of cognition: exploring representations and inductive biases , 2010, Trends in Cognitive Sciences.
[29] Adam N Sanborn,et al. Rational approximations to rational models: alternative algorithms for category learning. , 2010, Psychological review.
[30] James L. McClelland,et al. Letting structure emerge: connectionist and dynamical systems approaches to cognition , 2010, Trends in Cognitive Sciences.
[31] Samuel Gershman,et al. The Neural Costs of Optimal Control , 2010, NIPS.
[32] B. Love,et al. The myth of computational level theory and the vacuity of rational analysis , 2011, Behavioral and Brain Sciences.
[33] Charles Kemp,et al. How to Grow a Mind: Statistics, Structure, and Abstraction , 2011, Science.
[34] Joseph Y. Halpern,et al. Algorithmic rationality: adding cost of computation to game theory , 2011, SECO.
[35] Thomas L. Griffiths,et al. Exploring the influence of particle filter parameters on order effects in causal learning , 2011, CogSci.
[36] J. Bowers,et al. Bayesian just-so stories in psychology and neuroscience. , 2012, Psychological bulletin.
[37] Thomas L. Griffiths,et al. "Burn-in, bias, and the rationality of anchoring" , 2012, NIPS.
[38] David Tolpin,et al. Selecting Computations: Theory and Applications , 2012, UAI.
[39] Angela L. Duckworth,et al. An opportunity cost model of subjective effort and task performance. , 2013, The Behavioral and brain sciences.
[40] Ricardo Silva,et al. Constraining bridges between levels of analysis: A computational justification for locally Bayesian learning , 2013 .
[41] Noah D. Goodman,et al. Lieder,F, and Goodman, ND, and Huys, QJM (2013). Controllability and resource-rational planning. Cosyne Abstracts 2013, Salt Lake City USA. , 2013 .
[42] B. Newell. Judgment Under Uncertainty , 2013 .
[43] Vikash K. Mansinghka,et al. Reconciling intuitive physics and Newtonian mechanics for colliding objects. , 2013, Psychological review.
[44] Thomas Icard,et al. Toward Boundedly Rational Analysis , 2014, CogSci.
[45] Thomas L. Griffiths,et al. One and Done? Optimal Decisions From Very Few Samples , 2014, Cogn. Sci..
[46] Thomas L. Griffiths,et al. The high availability of extreme events serves resource-rational decision-making , 2014, CogSci.
[47] Satinder Singh,et al. Computational Rationality: Linking Mechanism and Behavior Through Bounded Utility Maximization , 2014, Top. Cogn. Sci..