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  1. Rational Foundations of Fast and Frugal Heuristics: The Ecological Rationality of Strategy Selection via Improper Linear Models.Jason Dana & Clintin P. Davis-Stober - 2016 - Minds and Machines 26 (1-2):61-86.
    Research on “improper” linear models has shown that predetermined weighting schemes for the linear model, such as equally weighting all predictors, can be surprisingly accurate on cross-validation. We review recent advances that can characterize the optimal choice of an improper linear model. We extend this research to the understanding of fast and frugal heuristics, particularly to the ecologically rational goal of understanding in which task environments given heuristics are optimal. We demonstrate how to test this model using the Recognition Heuristic (...)
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  • The consistency and ecological rationality approaches to normative bounded rationality.Nathan Berg - 2014 - Journal of Economic Methodology 21 (4):375-395.
    This paper focuses on tacit versus explicit uses of plural performance metrics as a primary methodological characteristic. This characteristic usefully distinguishes two schools of normative analysis and their approaches to normative interpretations of bounded rationality. Both schools of thought make normative claims about bounded rationality by comparing the performance of decision procedures using more than one performance metric. The consistency school makes tacit reference to performance metrics outside its primary axiomatic framework, but lexicographically promotes internal axiomatic consistency as the primary, (...)
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  • Heuristics, Descriptions, and the Scope of Mechanistic Explanation.Carlos Zednik - 2015 - In Pierre-Alain Braillard & Christophe Malaterre (eds.), Explanation in Biology. An Enquiry into the Diversity of Explanatory Patterns in the Life Sciences. Dordrecht: Springer. pp. 295-318.
    The philosophical conception of mechanistic explanation is grounded on a limited number of canonical examples. These examples provide an overly narrow view of contemporary scientific practice, because they do not reflect the extent to which the heuristic strategies and descriptive practices that contribute to mechanistic explanation have evolved beyond the well-known methods of decomposition, localization, and pictorial representation. Recent examples from evolutionary robotics and network approaches to biology and neuroscience demonstrate the increasingly important role played by computer simulations and mathematical (...)
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  • (1 other version)Methodology and Ontology in Microbiome Research.John Huss - 2014 - Biological Theory 9 (4):1-11.
    Research on the human microbiome has generated a staggering amount of sequence data, revealing variation in microbial diversity at the community, species (or phylotype), and genomic levels. In order to make this complexity more manageable and easier to interpret, new units—the metagenome, core microbiome, and enterotype—have been introduced in the scientific literature. Here, I argue that analytical tools and exploratory statistical methods, coupled with a translational imperative, are the primary drivers of this new ontology. By reducing the dimensionality of variation (...)
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  • Rational analysis: Too rational for comfort?Ronald de Sousa - 1991 - Behavioral and Brain Sciences 14 (3):492-492.
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  • Probabilistically Valid Inference of Covariation From a Single x,y Observation When Univariate Characteristics Are Known.Michael E. Doherty, Richard B. Anderson, Amanda M. Kelley & James H. Albert - 2009 - Cognitive Science 33 (2):183-205.
    Participants were asked to draw inferences about correlation from single x,y observations. In Experiment 1 statistically sophisticated participants were given the univariate characteristics of distributions of x and y and asked to infer whether a single x, y observation came from a correlated or an uncorrelated population. In Experiment 2, students with a variety of statistical backgrounds assigned posterior probabilities to five possible populations based on single x, y observations, again given knowledge of the univariate statistics. In Experiment 3, statistically (...)
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  • (1 other version)Homo Heuristicus: Why Biased Minds Make Better Inferences.Gerd Gigerenzer & Henry Brighton - 2009 - Topics in Cognitive Science 1 (1):107-143.
    Heuristics are efficient cognitive processes that ignore information. In contrast to the widely held view that less processing reduces accuracy, the study of heuristics shows that less information, computation, and time can in fact improve accuracy. We review the major progress made so far: the discovery of less-is-more effects; the study of the ecological rationality of heuristics, which examines in which environments a given strategy succeeds or fails, and why; an advancement from vague labels to computational models of heuristics; the (...)
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  • Why It Is Time To Move Beyond Nagelian Reduction.Marie I. Kaiser - 2012 - In D. Dieks, S. Hartmann, T. Uebel & M. Weber (eds.), Probabilities, Laws and Structure. Springer. pp. 255-272.
    In this paper I argue that it is finally time to move beyond the Nagelian framework and to break new ground in thinking about epistemic reduction in biology. I will do so, not by simply repeating all the old objections that have been raised against Ernest Nagel’s classical model of theory reduction. Rather, I grant that a proponent of Nagel’s approach can handle several of these problems but that, nevertheless, Nagel’s general way of thinking about epistemic reduction in terms of (...)
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  • Attention metaphors: How metaphors guide the cognitive psychology of attention.Diego Fernandez-Duque & Mark L. Johnson - 1999 - Cognitive Science 23 (1):83-116.
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  • Cognitive Metascience: A New Approach to the Study of Theories.Miłkowski Marcin - 2023 - Przeglad Psychologiczny 66 (1):185-207.
    In light of the recent credibility crisis in psychology, this paper argues for a greater emphasis on theorizing in scientific research. Although reliable experimental evidence, preregistration, methodological rigor, and new computational frameworks for modeling are important, scientific progress also relies on properly functioning theories. However, the current understanding of the role of theorizing in psychology is lacking, which may lead to future crises. Theories should not be viewed as mere speculations or simple inductive generalizations. To address this issue, the author (...)
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  • Arbitrating norms for reasoning tasks.Aliya R. Dewey - 2022 - Synthese 200 (6):1-26.
    The psychology of reasoning uses norms to categorize responses to reasoning tasks as correct or incorrect in order to interpret the responses and compare them across reasoning tasks. This raises the arbitration problem: any number of norms can be used to evaluate the responses to any reasoning task and there doesn’t seem to be a principled way to arbitrate among them. Elqayam and Evans have argued that this problem is insoluble, so they call for the psychology of reasoning to dispense (...)
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  • Testable or bust: theoretical lessons for predictive processing.Marcin Miłkowski & Piotr Litwin - 2022 - Synthese 200 (6):1-18.
    The predictive processing account of action, cognition, and perception is one of the most influential approaches to unifying research in cognitive science. However, its promises of grand unification will remain unfulfilled unless the account becomes theoretically robust. In this paper, we focus on empirical commitments of PP, since they are necessary both for its theoretical status to be established and for explanations of individual phenomena to be falsifiable. First, we argue that PP is a varied research tradition, which may employ (...)
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  • (3 other versions)Life, mind, agency: Why Markov blankets fail the test of evolution.Walter Veit & Heather Browning - 2022 - Behavioral and Brain Sciences 45:e214.
    There has been much criticism of the idea that Friston's free-energy principle can unite the life and mind sciences. Here, we argue that perhaps the greatest problem for the totalizing ambitions of its proponents is a failure to recognize the importance of evolutionary dynamics and to provide a convincing adaptive story relating free-energy minimization to organismal fitness.
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  • The emergence of objectivity: Fleck, Foucault, Kuhn and Hacking.Luca Sciortino - 2021 - Studies in History and Philosophy of Science Part A 88 (1):128-137.
    The analytical notions of ‘thought style’, ‘paradigm’, ‘episteme’ and ‘style of reasoning’ are some of the most popular frameworks in the history and philosophy of science. Although their proponents, Ludwik Fleck, Thomas Kuhn, Michel Foucault, and Ian Hacking, are all part of the same philosophical tradition that closely connects history and philosophy, the extent to which they share similar assumptions and objectives is still under debate. In the first part of the paper, I shall argue that, despite the fact that (...)
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  • Values in Psychometrics.Lisa D. Wijsen, Denny Borsboom & Anna Alexandrova - forthcoming - Perspectives on Psychological Science.
    When it originated in the late 19th century, psychometrics was a field with both a scientific and a social mission: psychometrics provided new methods for research into individual differences, and at the same time, these psychometric instruments were considered a means to create a new social order. In contrast, contemporary psychometrics - due to its highly technical nature and its limited involvement in substantive psychological research - has created the impression of being a value-free discipline. In this article, we develop (...)
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  • Epistemic Challenges: Engaging Philosophically in Cognitive Science.Przemysław R. Nowakowski - 2019 - Ruch Filozoficzny 75 (2):237.
    In this article, I show the role that the philosopher of cognitive science can cur-rently play in cognitive science research. I argue for the important, and not yet considered, role of the philosophy of cognitive science in cognitive science, that is, the importance of cooperation between philosophers of science with cogni-tive scientists in investigating the research methods and theoretical assump-tions of cognitive science. At the beginning of the paper I point out, how the philosopher of science, here, the philosopher of (...)
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  • La Mesure en psychologie de binet à Thurstone, 1900–1930.Olivier Martin - 1997 - Revue de Synthèse 118 (4):457-493.
    Le psychologue français Alfred Binet est à l'origine du développement de tests mentaux destinés à diagnostiquer le « niveau intellectuel » des enfants. Initialement conçus comme des tests cliniques, leur importation aux États-Unis dans les années 1910 a considérablement modifié leur usage, leur portée pratique et leur interprétation. Devenus les instruments de politiques eugéniques ou héréditaristes, utilisés dans des processus de sélection de grande échelle, les tests ont transformé la conception que les psychologues se faisaient de l'intelligence: initialement conçue comme (...)
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  • (1 other version)Bayesian Cognitive Science, Monopoly, and Neglected Frameworks.Matteo Colombo & Stephan Hartmann - 2015 - British Journal for the Philosophy of Science 68 (2):451–484.
    A widely shared view in the cognitive sciences is that discovering and assessing explanations of cognitive phenomena whose production involves uncertainty should be done in a Bayesian framework. One assumption supporting this modelling choice is that Bayes provides the best approach for representing uncertainty. However, it is unclear that Bayes possesses special epistemic virtues over alternative modelling frameworks, since a systematic comparison has yet to be attempted. Currently, it is then premature to assert that cognitive phenomena involving uncertainty are best (...)
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  • Bayesian reverse-engineering considered as a research strategy for cognitive science.Carlos Zednik & Frank Jäkel - 2016 - Synthese 193 (12):3951-3985.
    Bayesian reverse-engineering is a research strategy for developing three-level explanations of behavior and cognition. Starting from a computational-level analysis of behavior and cognition as optimal probabilistic inference, Bayesian reverse-engineers apply numerous tweaks and heuristics to formulate testable hypotheses at the algorithmic and implementational levels. In so doing, they exploit recent technological advances in Bayesian artificial intelligence, machine learning, and statistics, but also consider established principles from cognitive psychology and neuroscience. Although these tweaks and heuristics are highly pragmatic in character and (...)
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  • Probabilistic mental models: A Brunswikian theory of confidence.Gerd Gigerenzer, Ulrich Hoffrage & Heinz Kleinbölting - 1991 - Psychological Review 98 (4):506-528.
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  • Reasoning the fast and frugal way: Models of bounded rationality.Gerd Gigerenzer & Daniel Goldstein - 1996 - Psychological Review 103 (4):650-669.
    Humans and animals make inferences about the world under limited time and knowledge. In contrast, many models of rational inference treat the mind as a Laplacean Demon, equipped with unlimited time, knowledge, and computational might. Following H. Simon's notion of satisficing, the authors have proposed a family of algorithms based on a simple psychological mechanism: one-reason decision making. These fast and frugal algorithms violate fundamental tenets of classical rationality: They neither look up nor integrate all information. By computer simulation, the (...)
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  • Discovery in Cognitive Psychology: New Tools Inspire New Theories.Gerd Gigerenzer - 1992 - Science in Context 5 (2):329-350.
    The ArgumentScientific tools—measurement and calculation instruments, techniques of inference—straddle the line between the context of discovery and the context of justification. In discovery, new scientific tools suggest new theoretical metaphors and concepts; and in justification, these tool-derived theoretical metaphors and concepts are morelikely to be accepted by the scientific community if the tools are already entrenched in scientific practice.Techniques of statistical inference and hypothesis testing entered American psychology first as tools in the 1940s and 1950s and then as cognitive theories (...)
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  • Domain-specific reasoning: Social contracts, cheating, and perspective change.Gerd Gigerenzer & Klaus Hug - 1992 - Cognition 43 (2):127-171.
    What counts as human rationality: reasoning processes that embody content-independent formal theories, such as propositional logic, or reasoning processes that are well designed for solving important adaptive problems? Most theories of human reasoning have been based on content-independent formal rationality, whereas adaptive reasoning, ecological or evolutionary, has been little explored. We elaborate and test an evolutionary approach, Cosmides' social contract theory, using the Wason selection task. In the first part, we disentangle the theoretical concept of a “social contract” from that (...)
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  • Human cognition is an adaptive process.Gyan C. Agarwal - 1991 - Behavioral and Brain Sciences 14 (3):485-486.
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  • More on rational analysis.John R. Anderson - 1991 - Behavioral and Brain Sciences 14 (3):508-517.
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  • Optimality and psychological explanation.Peter Godfrey-Smith - 1991 - Behavioral and Brain Sciences 14 (3):496-497.
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  • Bayes in the context of suboptimality.Robert A. M. Gregson - 1991 - Behavioral and Brain Sciences 14 (3):497-498.
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  • Rational analysis and the Lens model.Reid Hastie & Kenneth R. Hammond - 1991 - Behavioral and Brain Sciences 14 (3):498-498.
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  • Adaptive rationality and identifiability of psychological processes.Dominic W. Massaro & Daniel Friedman - 1991 - Behavioral and Brain Sciences 14 (3):499-501.
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  • Rational analysis will not throw off the yoke of the precision-importance trade-off function.Wolfgang Schwarz - 1991 - Behavioral and Brain Sciences 14 (3):501-502.
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  • The rationality of causal inference.Thomas R. Shultz - 1991 - Behavioral and Brain Sciences 14 (3):503-504.
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  • But how does the brain think?Steven L. Small - 1991 - Behavioral and Brain Sciences 14 (3):504-505.
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  • Adaptivity and rational analysis.Bradley W. Dickinson - 1991 - Behavioral and Brain Sciences 14 (3):492-493.
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  • Rational analysis and illogical inference.Edmund Fantino & Stephanie Stolarz-Fantino - 1991 - Behavioral and Brain Sciences 14 (3):494-494.
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  • Moderate Epistemic Relativism and Our Epistemic Goals.Jonathan M. Weinberg - 2007 - Episteme 4 (1):66-92.
    Although radical forms of relativism are perhaps beyond the epistemological pale, I argue here that a more moderate form may be plausible, and articulate the conditions under which moderate epistemic relativism could well serve our epistemic goals. In particular, as a result of our limitations as human cognizers, we find ourselves needing to investigate the dappled and difficult world by means of competing communities of highly specialized researchers. We would do well, I argue, to admit of the existence of unresolvable (...)
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  • Using Multilevel Models to Estimate Variation in Foraging Returns.Richard McElreath & Jeremy Koster - 2014 - Human Nature 25 (1):100-120.
    Distributions of human foraging success across age have implications for many aspects of human evolution. Estimating the distribution of foraging returns is complicated by (1) the zero-inflated nature of hunting returns, as many if not most trips fail, and (2) the substantial variation among hunters, independent of age. We develop a multilevel mixture analysis of human foraging data to address these difficulties. Using a previously published 20-year record of hunts by 147 individual Aché hunters in eastern Paraguay, we estimate returns-by-age (...)
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  • If nudge cannot be applied: a litmus test of the readers’ stance on paternalism. [REVIEW]Chen Li, Zhihua Li & Peter P. Wakker - 2014 - Theory and Decision 76 (3):297-315.
    A central question in many debates on paternalism is whether a decision analyst can ever go against the stated preference of a client, even if merely intending to improve the decisions for the client. Using four gedanken-experiments, this paper shows that this central question, so cleverly and aptly avoided by libertarian paternalism (nudge), cannot always be avoided. The four thought experiments, while purely hypothetical, serve to raise and specify the critical arguments in a maximally clear and pure manner. The first (...)
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  • Comorbidity: A network perspective.Angélique Oj Cramer, Lourens J. Waldorp, Han Lj van der Maas & Denny Borsboom - 2010 - Behavioral and Brain Sciences 33 (2-3):137-150.
    The pivotal problem of comorbidity research lies in the psychometric foundation it rests on, that is, latent variable theory, in which a mental disorder is viewed as a latent variable that causes a constellation of symptoms. From this perspective, comorbidity is a (bi)directional relationship between multiple latent variables. We argue that such a latent variable perspective encounters serious problems in the study of comorbidity, and offer a radically different conceptualization in terms of a network approach, where comorbidity is hypothesized to (...)
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  • Explanation in Biology: An Enquiry into the Diversity of Explanatory Patterns in the Life Sciences.P.-A. Braillard and C. Malaterre (ed.) - 2015 - Springer.
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  • Revitalizing the metaphoric process in commonsense psychology.Wan-Chi Wong - 2002 - Philosophical Psychology 15 (4):473 – 488.
    In response to the increasingly acknowledged power of metaphor upon everyday and scientific thinking, the present essay aims to revitalize the metaphoric process in commonsense psychology from the interaction view perspective. As prerequisites, a historical review of the "man-the-scientist" metaphor inherited in commonsense psychology, and a situation analysis of its dormant state are attempted. With metaphorical imagination, a holistic-paradigmatic view of personal theories is postulated on the basis of new knowledge in the philosophy and history of science, namely, the Duhem (...)
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  • How to Explain Behavior?Gerd Gigerenzer - 2020 - Topics in Cognitive Science 12 (4):1363-1381.
    Unlike behaviorism, cognitive psychology relies on mental concepts to explain behavior. Yet mental processes are not directly observable and multiple explanations are possible, which poses a challenge for finding a useful framework. In this article, I distinguish three new frameworks for explanations that emerged after the cognitive revolution. The first is called tools‐to‐theories: Psychologists' new tools for data analysis, such as computers and statistics, are turned into theories of mind. The second proposes as‐if theories: Expected utility theory and Bayesian statistics (...)
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  • (1 other version)Viewing “p” through the lens of the philosophy of medicine.Sara Asato & James Giordano - 2019 - Philosophy, Ethics, and Humanities in Medicine 14 (1):1-3.
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  • Beware of samples! A cognitive-ecological sampling approach to judgment biases.Klaus Fiedler - 2000 - Psychological Review 107 (4):659-676.
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  • The Oxford Handbook of Causal Reasoning.Michael Waldmann (ed.) - 2017 - Oxford, England: Oxford University Press.
    Causal reasoning is one of our most central cognitive competencies, enabling us to adapt to our world. Causal knowledge allows us to predict future events, or diagnose the causes of observed facts. We plan actions and solve problems using knowledge about cause-effect relations. Without our ability to discover and empirically test causal theories, we would not have made progress in various empirical sciences. In the past decades, the important role of causal knowledge has been discovered in many areas of cognitive (...)
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  • On the nonapplicability of a rational analysis to human cognition.Eldar Shafir - 1991 - Behavioral and Brain Sciences 14 (3):502-503.
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  • A Bayesian theory of thought.Howard Smokler - 1991 - Behavioral and Brain Sciences 14 (3):505-505.
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  • Does the environment have the same structure as Bayes' theorem?Gerd Gigerenzer - 1991 - Behavioral and Brain Sciences 14 (3):495-496.
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  • The cognitive laboratory, the library and the Skinner box.Howard Rachlin - 1991 - Behavioral and Brain Sciences 14 (3):501-501.
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  • Normative theories of categorization.James E. Corter - 1991 - Behavioral and Brain Sciences 14 (3):491-492.
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  • Optimality as an epistemological organizing principle.Gideon Keren - 1993 - Behavioral and Brain Sciences 16 (3):622-623.
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