35 found
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  1.  32
    Search of associative memory.Jeroen G. Raaijmakers & Richard M. Shiffrin - 1981 - Psychological Review 88 (2):93-134.
  2.  32
    A retrieval model for both recognition and recall.Gary Gillund & Richard M. Shiffrin - 1984 - Psychological Review 91 (1):1-67.
  3. (2 other versions)Controlled and automatic human information processing: I.Walter E. Schneider & Richard M. Shiffrin - 1977 - Detection, Search, and Attention. Psychological Review 84:1-66.
  4.  59
    A Survey of Model Evaluation Approaches With a Tutorial on Hierarchical Bayesian Methods.Richard M. Shiffrin, Michael D. Lee, Woojae Kim & Eric-Jan Wagenmakers - 2008 - Cognitive Science 32 (8):1248-1284.
    This article reviews current methods for evaluating models in the cognitive sciences, including theoretically based approaches, such as Bayes factors and minimum description length measures; simulation approaches, including model mimicry evaluations; and practical approaches, such as validation and generalization measures. This article argues that, although often useful in specific settings, most of these approaches are limited in their ability to give a general assessment of models. This article argues that hierarchical methods, generally, and hierarchical Bayesian methods, specifically, can provide a (...)
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  5.  54
    Altering object representations through category learning.Robert L. Goldstone, Yvonne Lippa & Richard M. Shiffrin - 2001 - Cognition 78 (1):27-43.
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  6.  21
    Rehearsal and storage of visual information.William Shaffer & Richard M. Shiffrin - 1972 - Journal of Experimental Psychology 92 (2):292.
  7.  62
    Visual processing capacity and attentional control.Richard M. Shiffrin & Gerald T. Gardner - 1972 - Journal of Experimental Psychology 93 (1):72.
  8.  23
    Perception and preference in short-term word priming.David E. Huber, Richard M. Shiffrin, Keith B. Lyle & Kirsten I. Ruys - 2001 - Psychological Review 108 (1):149-182.
  9.  20
    Seven plus or minus two: A commentary on capacity limitations.Richard M. Shiffrin & Robert M. Nosofsky - 1994 - Psychological Review 101 (2):357-361.
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  10.  94
    Actively Learning Object Names Across Ambiguous Situations.George Kachergis, Chen Yu & Richard M. Shiffrin - 2013 - Topics in Cognitive Science 5 (1):200-213.
    Previous research shows that people can use the co-occurrence of words and objects in ambiguous situations (i.e., containing multiple words and objects) to learn word meanings during a brief passive training period (Yu & Smith, 2007). However, learners in the world are not completely passive but can affect how their environment is structured by moving their heads, eyes, and even objects. These actions can indicate attention to a language teacher, who may then be more likely to name the attended objects. (...)
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  11.  33
    Automatic and controlled processing revisited.Richard M. Shiffrin & Walter Schneider - 1984 - Psychological Review 91 (2):269-276.
  12.  35
    A dynamic approach to recognition memory.Gregory E. Cox & Richard M. Shiffrin - 2017 - Psychological Review 124 (6):795-860.
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  13.  26
    A Bayesian model for implicit effects in perceptual identification.Lael J. Schooler, Richard M. Shiffrin & Jeroen G. W. Raaijmakers - 2001 - Psychological Review 108 (1):257-272.
  14.  30
    Discrete-slots models of visual working-memory response times.Christopher Donkin, Robert M. Nosofsky, Jason M. Gold & Richard M. Shiffrin - 2013 - Psychological Review 120 (4):873-902.
  15.  99
    Modeling memory and perception.Richard M. Shiffrin - 2003 - Cognitive Science 27 (3):341-378.
    I present a framework for modeling memory, retrieval, perception, and their interactions. Recent versions of the models were inspired by Bayesian induction: We chose models that make optimal decisions conditioned on a memory/perceptual system with inherently noisy storage and retrieval. The resultant models are, fortunately, largely consistent with my models dating back to the 1960s, and are therefore natural successors. My recent articles have presented simplified models in order to focus on particular applications. This article takes a larger perspective and (...)
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  16.  26
    Building permanent memory codes: codification and repetition effects in word identification.Aita Salasoo, Richard M. Shiffrin & Timothy C. Feustel - 1985 - Journal of Experimental Psychology 114 (1).
  17.  17
    Attention, automatism, and consciousness.Richard M. Shiffrin - 1997 - In Jonathan D. Cohen & Jonathan W. Schooler (eds.), Scientific Approaches to Consciousness. Lawrence Erlbaum. pp. 49--64.
  18.  30
    Information persistence in short-term memory.Richard M. Shiffrin - 1973 - Journal of Experimental Psychology 100 (1):39.
  19.  16
    The co-evolution of knowledge and event memory.Angela B. Nelson & Richard M. Shiffrin - 2013 - Psychological Review 120 (2):356-394.
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  20.  45
    What are the appropriate axioms of rationality for reasoning under uncertainty with resource-constrained systems?Harald Atmanspacher, Irina Basieva, Jerome R. Busemeyer, Andrei Y. Khrennikov, Emmanuel M. Pothos, Richard M. Shiffrin & Zheng Wang - 2020 - Behavioral and Brain Sciences 43.
    When constrained by limited resources, how do we choose axioms of rationality? The target article relies on Bayesian reasoning that encounter serioustractabilityproblems. We propose another axiomatic foundation: quantum probability theory, which provides for less complex and more comprehensive descriptions. More generally, defining rationality in terms of axiomatic systems misses a key issue: rationality must be defined by humans facing vague information.
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  21. Perspectives on Modeling in Cognitive Science.Richard M. Shiffrin - 2010 - Topics in Cognitive Science 2 (4):736-750.
    This commentary gives a personal perspective on modeling and modeling developments in cognitive science, starting in the 1950s, but focusing on the author’s personal views of modeling since training in the late 1960s, and particularly focusing on advances since the official founding of the Cognitive Science Society. The range and variety of modeling approaches in use today are remarkable, and for many, bewildering. Yet to come to anything approaching adequate insights into the infinitely complex fields of mind, brain, and intelligent (...)
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  22. Criterion Setting and the Dynamics of Recognition Memory.Gregory E. Cox & Richard M. Shiffrin - 2012 - Topics in Cognitive Science 4 (1):135-150.
    Models of recognition memory have traditionally struggled with the puzzle of criterion setting, a problem that is particularly acute in cases in which items for study and test are of widely varying types, with differing degrees of baseline familiarity and experience (e.g., words vs. random dot patterns). We present a dynamic model of the recognition process that addresses the criterion setting problem and produces joint predictions for choice and reaction time. In this model, recognition decisions are based not on the (...)
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  23.  27
    Context Noise and Item Noise Jointly Determine Recognition Memory: A Comment on Dennis and Humphreys (2001).Amy H. Criss & Richard M. Shiffrin - 2004 - Psychological Review 111 (3):800-807.
  24. Cross-situational statistical learning: Implicit or intentional.George Kachergis, Chen Yu & Richard M. Shiffrin - 2010 - In S. Ohlsson & R. Catrambone (eds.), Proceedings of the 32nd Annual Conference of the Cognitive Science Society. Cognitive Science Society. pp. 1189--1194.
  25.  13
    Against naïve induction from experimental data.David Kellen, Gregory E. Cox, Chris Donkin, John C. Dunn & Richard M. Shiffrin - 2024 - Behavioral and Brain Sciences 47:e51.
    This commentary argues against the indictment of current experimental practices such as piecemeal testing, and the proposed integrated experiment design (IED) approach, which we see as yet another attempt at automating scientific thinking. We identify a number of undesirable features of IED that lead us to believe that its broad application will hinder scientific progress.
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  26.  19
    Models of memory.Jeroen Gw Raaijmakers & Richard M. Shiffrin - 2002 - In J. Wixted & H. Pashler (eds.), Stevens' Handbook of Experimental Psychology. Wiley.
  27.  15
    Categorization (restructuring) and automatization: Two separable factors.Walter Schneider & Richard M. Shiffrin - 1985 - Psychological Review 92 (3):424-428.
  28.  15
    The distinction between long-term knowledge and short-term control processes is valid and useful.Richard M. Shiffrin, Walter Schneider & Gordon D. Logan - 2023 - Behavioral and Brain Sciences 46:e140.
    The binary distinction De Neys questions has been put forward many times since the beginnings of psychology, in slightly different forms and under different names. It has proved enormously useful and has received detailed empirical support and careful modeling. At heart the distinction is that between knowledge in long-term memory and control processes in short-term memory.
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  29. Adaptive constraints and inference in cross-situational word learning.George Kachergis, Chen Yu & Richard M. Shiffrin - 2010 - In S. Ohlsson & R. Catrambone (eds.), Proceedings of the 32nd Annual Conference of the Cognitive Science Society. Cognitive Science Society. pp. 2464--2469.
     
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  30. Prior knowledge bootstraps cross-situational learning.Krystal A. Klein, Chen Yu & Richard M. Shiffrin - 2008 - In B. C. Love, K. McRae & V. M. Sloutsky (eds.), Proceedings of the 30th Annual Conference of the Cognitive Science Society. Cognitive Science Society. pp. 1930--5.
  31.  25
    Repetitions, blank trials, and the vonRestorff effect in free recall memory.George R. Potts & Richard M. Shiffrin - 1970 - Journal of Experimental Psychology 86 (1):128.
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  32.  44
    Models versus descriptions: Real differences and language differences.Jeroen G. W. Raaijmakers & Richard M. Shiffrin - 2003 - Behavioral and Brain Sciences 26 (6):753-753.
    We argue that an approach that treats short-term memory as activated long-term memory is not inherently in conflict with information recycling in a limited-capacity or working-memory store, or with long-term storage based on the processing in such a store. Language differences aside, real model differences can only be assessed when the contrasting models are formulated precisely.
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  33.  6
    Remi and Rouse: Quantitative Models for Long-Term and Short-Term Priming in Perceptual Identification.Lael J. Schooler, Eric-Jan M. Wagenmakers, Jeroen G. W. Raaijmakers, Richard M. Shiffrin, Dave Huber & RenÉ Zeelenberg - 2002 - In Jeffrey S. Bowers & Chad J. Marsolek (eds.), Rethinking Implicit Memory. Oxford University Press UK.
    This chapter presents two models of priming. The primary task under consideration is the identification of words presented visually at threshold. The first model, REMI, is a model for long-term priming in implicit memory. It explains repetition priming effects by assuming that during study of a word some contextual information is added to the corresponding lexical trace. This contextual information stored during the study task will tend to match the contextual information present during the test task, leading subjects to prefer (...)
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  34.  25
    Is it Reasonable to Study Decision‐Making Quantitatively?Richard M. Shiffrin - 2022 - Topics in Cognitive Science 14 (3):621-633.
    Topics in Cognitive Science, Volume 14, Issue 3, Page 621-633, July 2022.
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  35.  48
    Locally rational decision-making.Richard M. Shiffrin - 2003 - Behavioral and Brain Sciences 26 (2):175-175.
    Colman shows that normative theories of rational decision-making fail to produce rational decisions in simple interactive games. I suggest that well-formed theories are possible in local settings, keeping in mind that a good part of each game is the generation of a rational approach appropriate for that game. The key is rationality defined in terms of the game, not individual decisions.
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