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  1. Calibrating Generative Models: The Probabilistic Chomsky-Schützenberger Hierarchy.Thomas Icard - 2020 - Journal of Mathematical Psychology 95.
    A probabilistic Chomsky–Schützenberger hierarchy of grammars is introduced and studied, with the aim of understanding the expressive power of generative models. We offer characterizations of the distributions definable at each level of the hierarchy, including probabilistic regular, context-free, (linear) indexed, context-sensitive, and unrestricted grammars, each corresponding to familiar probabilistic machine classes. Special attention is given to distributions on (unary notations for) positive integers. Unlike in the classical case where the "semi-linear" languages all collapse into the regular languages, using analytic tools (...)
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  • Communication and content.Prashant Parikh - 2019 - Berlin, Germany: Language Science Press.
    Communication and content presents a comprehensive and foundational account of meaning based on new versions of situation theory and game theory. The literal and implied meanings of an utterance are derived from first principles assuming little more than the partial rationality of interacting agents. New analyses of a number of diverse phenomena – a wide notion of ambiguity and content encompassing phonetics, syntax, semantics, pragmatics, and beyond, vagueness, convention and conventional meaning, indeterminacy, universality, the role of truth in communication, semantic (...)
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  • Multialternative decision by sampling: A model of decision making constrained by process data.Takao Noguchi & Neil Stewart - 2018 - Psychological Review 125 (4):512-544.
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  • Extinction of likes and dislikes: effects of feature-specific attention allocation.Jolien Vanaelst, Adriaan Spruyt, Tom Everaert & Jan De Houwer - 2017 - Cognition and Emotion 31 (8):1595-1609.
    The evaluative conditioning effect refers to the change in the liking of a neutral stimulus due to its pairing with another stimulus. We examined whether the extinction rate of the EC effect is moderated by feature-specific attention allocation. In two experiments, CSs were abstract Gabor patches varying along two orthogonal, perceptual dimensions. During the acquisition phase, one of these dimensions was predictive of the valence of the USs. During the extinction phase, CSs were presented alone and participants were asked to (...)
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  • Rational approximations to rational models: Alternative algorithms for category learning.Adam N. Sanborn, Thomas L. Griffiths & Daniel J. Navarro - 2010 - Psychological Review 117 (4):1144-1167.
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  • The overlap model: A model of letter position coding.Pablo Gomez, Roger Ratcliff & Manuel Perea - 2008 - Psychological Review 115 (3):577-600.
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  • A neurobiological theory of automaticity in perceptual categorization.F. Gregory Ashby, John M. Ennis & Brian J. Spiering - 2007 - Psychological Review 114 (3):632-656.
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  • Absolute Identification by Relative Judgment.Neil Stewart, Gordon D. A. Brown & Nick Chater - 2005 - Psychological Review 112 (4):881-911.
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  • Information-accumulation theory of speeded categorization.Koen Lamberts - 2000 - Psychological Review 107 (2):227-260.
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  • Connectionist and diffusion models of reaction time.Roger Ratcliff, Trisha Van Zandt & Gail McKoon - 1999 - Psychological Review 106 (2):261-300.
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  • Instance‐based learning in dynamic decision making.Cleotilde Gonzalez, Javier F. Lerch & Christian Lebiere - 2003 - Cognitive Science 27 (4):591-635.
    This paper presents a learning theory pertinent to dynamic decision making (DDM) called instancebased learning theory (IBLT). IBLT proposes five learning mechanisms in the context of a decision‐making process: instance‐based knowledge, recognition‐based retrieval, adaptive strategies, necessity‐based choice, and feedback updates. IBLT suggests in DDM people learn with the accumulation and refinement of instances, containing the decision‐making situation, action, and utility of decisions. As decision makers interact with a dynamic task, they recognize a situation according to its similarity to past instances, (...)
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  • Sequential sampling models of human text classification.Michael D. Lee & Elissa Y. Corlett - 2003 - Cognitive Science 27 (2):159-193.
    Text classification involves deciding whether or not a document is about a given topic. It is an important problem in machine learning, because automated text classifiers have enormous potential for application in information retrieval systems. It is also an interesting problem for cognitive science, because it involves real world human decision making with complicated stimuli. This paper develops two models of human text document classification based on random walk and accumulator sequential sampling processes. The models are evaluated using data from (...)
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  • Race-Specific Perceptual Discrimination Improvement Following Short Individuation Training With Faces.Rankin W. McGugin, James W. Tanaka, Sophie Lebrecht, Michael J. Tarr & Isabel Gauthier - 2011 - Cognitive Science 35 (2):330-347.
    This study explores the effect of individuation training on the acquisition of race-specific expertise. First, we investigated whether practice individuating other-race faces yields improvement in perceptual discrimination for novel faces of that race. Second, we asked whether there was similar improvement for novel faces of a different race for which participants received equal practice, but in an orthogonal task that did not require individuation. Caucasian participants were trained to individuate faces of one race (African American or Hispanic) and to make (...)
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  • A Neural Theory of Visual Attention: Bridging Cognition and Neurophysiology.Claus Bundesen, Thomas Habekost & Søren Kyllingsbæk - 2005 - Psychological Review 112 (2):291-328.
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  • Outlines of a multiple trace theory of temporal preparation.Sander A. Los, Wouter Kruijne & Martijn Meeter - 2014 - Frontiers in Psychology 5.
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  • Exemplar effects in categorization and multiple-cue judgment.Peter Juslin, Henrik Olsson & Anna-Carin Olsson - 2003 - Journal of Experimental Psychology: General 132 (1):133.
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  • Conceptual complexity and the bias/variance tradeoff.Erica Briscoe & Jacob Feldman - 2011 - Cognition 118 (1):2-16.
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  • Studying judgement: General issues.Nigel Harvey - 2001 - Thinking and Reasoning 7 (1):103 – 118.
    The previous papers raise a number of issues. How should we develop task typologies both to separate judgement from related cognitive tasks and to classify tasks within the judgement domain? Are there grounds for selecting between models of judgement when empirical tests fail to do so? What techniques can be used to find out more about the cognitive processes underlying judgement behaviour? I discuss these issues and give a brief assessment of the current state of play in this rapidly changing (...)
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  • Sequential sampling model for multiattribute choice alternatives with random attention time and processing order.Adele Diederich & Peter Oswald - 2014 - Frontiers in Human Neuroscience 8.
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  • Logical-rule models of classification response times: A synthesis of mental-architecture, random-walk, and decision-bound approaches.Mario Fific, Daniel R. Little & Robert M. Nosofsky - 2010 - Psychological Review 117 (2):309-348.
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  • Two-stage dynamic signal detection: A theory of choice, decision time, and confidence.Timothy J. Pleskac & Jerome R. Busemeyer - 2010 - Psychological Review 117 (3):864-901.
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  • Eye movements reveal memory processes during similarity- and rule-based decision making.Agnes Scholz, Bettina von Helversen & Jörg Rieskamp - 2015 - Cognition 136 (C):228-246.
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  • (1 other version)Modeling individual differences in working memory performance: a source activation account.Lynne M. Reder Larry Z. Daily, Marsha C. Lovett - 2001 - Cognitive Science 25 (3):315.
    Working memory resources are needed for processing and maintenance of information during cognitive tasks. Many models have been developed to capture the effects of limited working memory resources on performance. However, most of these models do not account for the finding that different individuals show different sensitivities to working memory demands, and none of the models predicts individual subjects' patterns of performance. We propose a computational model that accounts for differences in working memory capacity in terms of a quantity called (...)
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  • RACE/A: An Architectural Account of the Interactions Between Learning, Task Control, and Retrieval Dynamics.Leendert van Maanen, Hedderik van Rijn & Niels Taatgen - 2012 - Cognitive Science 36 (1):62-101.
    This article discusses how sequential sampling models can be integrated in a cognitive architecture. The new theory Retrieval by Accumulating Evidence in an Architecture (RACE/A) combines the level of detail typically provided by sequential sampling models with the level of task complexity typically provided by cognitive architectures. We will use RACE/A to model data from two variants of a picture–word interference task in a psychological refractory period design. These models will demonstrate how RACE/A enables interactions between sequential sampling and long-term (...)
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  • Hybrid and pluralist accounts of concepts: Processing and long-term storage, two dimensions of agreement.Sabrina Haimovici - 2023 - Philosophical Psychology 36 (3):601-620.
    Hybrid and pluralist accounts of concepts agree that the class of concepts includes a multiplicity of heterogeneous representational structures, such as prototypes, sets of exemplars and theories. In this paper I argue that these accounts agree on two additional central claims related to the ways in which they articulate those structures: each type of representational structure can be used independently in psychological processes, and co-referential concepts are associated in a distinctive way as representations of the same category. Although they disagree (...)
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  • A Computational Model of Context‐Dependent Encodings During Category Learning.Paulo F. Carvalho & Robert L. Goldstone - 2022 - Cognitive Science 46 (4).
    Cognitive Science, Volume 46, Issue 4, April 2022.
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  • A dynamic approach to recognition memory.Gregory E. Cox & Richard M. Shiffrin - 2017 - Psychological Review 124 (6):795-860.
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  • Bayesian Fundamentalism or Enlightenment? On the explanatory status and theoretical contributions of Bayesian models of cognition.Matt Jones & Bradley C. Love - 2011 - Behavioral and Brain Sciences 34 (4):169-188.
    The prominence of Bayesian modeling of cognition has increased recently largely because of mathematical advances in specifying and deriving predictions from complex probabilistic models. Much of this research aims to demonstrate that cognitive behavior can be explained from rational principles alone, without recourse to psychological or neurological processes and representations. We note commonalities between this rational approach and other movements in psychology – namely, Behaviorism and evolutionary psychology – that set aside mechanistic explanations or make use of optimality assumptions. Through (...)
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  • PROBabilities from EXemplars (PROBEX): a “lazy” algorithm for probabilistic inference from generic knowledge.Peter Juslin & Magnus Persson - 2002 - Cognitive Science 26 (5):563-607.
    PROBEX (PROBabilities from EXemplars), a model of probabilistic inference and probability judgment based on generic knowledge is presented. Its properties are that: (a) it provides an exemplar model satisfying bounded rationality; (b) it is a “lazy” algorithm that presumes no pre‐computed abstractions; (c) it implements a hybrid‐representation, similarity‐graded probability. We investigate the ecological rationality of PROBEX and find that it compares favorably with Take‐The‐Best and multiple regression (Gigerenzer, Todd, & the ABC Research Group, 1999). PROBEX is fitted to the point (...)
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  • An instance theory of attention and memory.Gordon D. Logan - 2002 - Psychological Review 109 (2):376-400.
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  • Executive control of visual attention in dual-task situations.Gordon D. Logan & Robert D. Gordon - 2001 - Psychological Review 108 (2):393-434.
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  • Logical-rules and the classification of integral dimensions: individual differences in the processing of arbitrary dimensions.Anthea G. Blunden, Tony Wang, David W. Griffiths & Daniel R. Little - 2014 - Frontiers in Psychology 5.
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  • The construction of categorization judgments: Using subjective confidence and response latency to test a distributed model.Asher Koriat & Hila Sorka - 2015 - Cognition 134 (C):21-38.
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  • Conceptual illusions.Geoffrey P. Goodwin & P. N. Johnson-Laird - 2010 - Cognition 114 (2):253-265.
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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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  • Time-varying boundaries for diffusion models of decision making and response time.Shunan Zhang, Michael D. Lee, Joachim Vandekerckhove, Gunter Maris & Eric-Jan Wagenmakers - 2014 - Frontiers in Psychology 5:112331.
    Diffusion models are widely-used and successful accounts of the time course of two-choice decision making. Most diffusion models assume constant boundaries, which are the threshold levels of evidence that must be sampled from a stimulus to reach a decision. We summarize theoretical results from statistics that relate distributions of decisions and response times to diffusion models with time-varying boundaries. We then develop a computational method for finding time-varying boundaries from empirical data, and apply our new method to two problems. The (...)
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  • The acquisition of Boolean concepts.Geoffrey P. Goodwin & Philip N. Johnson-Laird - 2013 - Trends in Cognitive Sciences 17 (3):128-133.
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  • Cognitive Control: Componential or Emergent?Richard P. Cooper - 2010 - Topics in Cognitive Science 2 (4):598-613.
    The past 25 years have witnessed an increasing awareness of the importance of cognitive control in the regulation of complex behavior. It now sits alongside attention, memory, language, and thinking as a distinct domain within cognitive psychology. At the same time it permeates each of these sibling domains. This introduction reviews recent work on cognitive control in an attempt to provide a context for the fundamental question addressed within this topic: Is cognitive control to be understood as resulting from the (...)
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  • The nature of Garner interference: The role of uncertainty, information, and variation in the breakdown in selective attention.Lior Niv, Rani Moran & Daniel Algom - 2022 - Cognition 218 (C):104950.
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  • Latent Factors in Attention Emerge from 9 Years of Age among Elementary School Children.Tao Ting, Wang Ligang, Fan Chunlei, Gao Wenbin & Shi Jiannong - 2017 - Frontiers in Psychology 8.
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  • Exemplars, Prototypes, Similarities, and Rules in Category Representation: An Example of Hierarchical Bayesian Analysis.Michael D. Lee & Wolf Vanpaemel - 2008 - Cognitive Science 32 (8):1403-1424.
    This article demonstrates the potential of using hierarchical Bayesian methods to relate models and data in the cognitive sciences. This is done using a worked example that considers an existing model of category representation, the Varying Abstraction Model (VAM), which attempts to infer the representations people use from their behavior in category learning tasks. The VAM allows for a wide variety of category representations to be inferred, but this article shows how a hierarchical Bayesian analysis can provide a unifying explanation (...)
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  • A dual-stage two-phase model of selective attention.Ronald Hübner, Marco Steinhauser & Carola Lehle - 2010 - Psychological Review 117 (3):759-784.
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  • A Conceptual and Psychometric Framework for Distinguishing Categories and Dimensions.Paul De Boeck, Mark Wilson & G. Scott Acton - 2005 - Psychological Review 112 (1):129-158.
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  • The Collapsing Choice Theory: Dissociating Choice and Judgment in Decision Making. [REVIEW]Jeffrey M. Stibel, Itiel E. Dror & Talia Ben-Zeev - 2009 - Theory and Decision 66 (2):149-179.
    Decision making theory in general, and mental models in particular, associate judgment and choice. Decision choice follows probability estimates and errors in choice derive mainly from errors in judgment. In the studies reported here we use the Monty Hall dilemma to illustrate that judgment and choice do not always go together, and that such a dissociation can lead to better decision-making. Specifically, we demonstrate that in certain decision problems, exceeding working memory limitations can actually improve decision choice. We show across (...)
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  • The CODE theory of visual attention: An integration of space-based and object-based attention.Gordon D. Logan - 1996 - Psychological Review 103 (4):603-649.
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  • Feature-sampling and random-walk models of individual-stimulus recognition.Koen Lamberts, Noellie Brockdorff & Evan Heit - 2003 - Journal of Experimental Psychology: General 132 (3):351.
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  • Human Semi-Supervised Learning.Bryan R. Gibson, Timothy T. Rogers & Xiaojin Zhu - 2013 - Topics in Cognitive Science 5 (1):132-172.
    Most empirical work in human categorization has studied learning in either fully supervised or fully unsupervised scenarios. Most real-world learning scenarios, however, are semi-supervised: Learners receive a great deal of unlabeled information from the world, coupled with occasional experiences in which items are directly labeled by a knowledgeable source. A large body of work in machine learning has investigated how learning can exploit both labeled and unlabeled data provided to a learner. Using equivalences between models found in human categorization and (...)
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  • DFT-D: a cognitive-dynamical model of dynamic decision making.Jared M. Hotaling & Jerome R. Busemeyer - 2012 - Synthese 189 (S1):67-80.
    The study of decision making has traditionally been dominated by axiomatic utility theories. More recently, an alternative approach, which focuses on the micro-mechanisms of the underlying deliberation process, has been shown to account for several "paradoxes" in human choice behavior for which simple utility-based approaches cannot. Decision field theory (DFT) is a cognitive-dynamical model of decision making and preferential choice, built on the fundamental principle that decisions are based on the accumulation of subjective evaluations of choice alternatives until a threshold (...)
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  • An integrated model of choices and response times in absolute identification.Scott D. Brown, A. A. J. Marley, Christopher Donkin & Andrew Heathcote - 2008 - Psychological Review 115 (2):396-425.
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  • The Dynamics of Scaling: A Memory-Based Anchor Model of Category Rating and Absolute Identification.Alexander A. Petrov & John R. Anderson - 2005 - Psychological Review 112 (2):383-416.
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