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Associationist Theories of Thought

Stanford Encyclopedia of Philosophy (2015)

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  1. Alief and belief.Tamar Gendler - 2018 - In Jeremy Fantl, Matthew McGrath & Ernest Sosa (eds.), Contemporary epistemology: an anthology. Hoboken, NJ: Wiley.
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  • Thinking, Fast and Slow.Daniel Kahneman - 2011 - New York: New York: Farrar, Straus and Giroux.
    In the international bestseller, Thinking, Fast and Slow, Daniel Kahneman, the renowned psychologist and winner of the Nobel Prize in Economics, takes us on a groundbreaking tour of the mind and explains the two systems that drive the way we think. System 1 is fast, intuitive, and emotional; System 2 is slower, more deliberative, and more logical. The impact of overconfidence on corporate strategies, the difficulties of predicting what will make us happy in the future, the profound effect of cognitive (...)
  • The Varieties of Reference.Gareth Evans - 1982 - Oxford: Oxford University Press. Edited by John Henry McDowell.
  • In Two Minds: Dual Processes and Beyond.Jonathan St B. T. Evans & Keith Frankish (eds.) - 2009 - Oxford University Press.
    This book explores the idea that we have two minds - one automatic, unconscious, and fast, the other controlled, conscious, and slow. It brings together leading researchers on dual-process theory to summarize the state of the art highlight key issues, present different perspectives, and provide a stimulus to further work.
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  • A model of dual attitudes.Timothy D. Wilson, Samuel Lindsey & Tonya Y. Schooler - 2000 - Psychological Review 107 (1):101-126.
    When an attitude changes from A₁ to A₂, what happens to A₁? Most theories assume, at least implicitly, that the new attitude replaces the former one. The authors argue that a new attitude can override, but not replace, the old one, resulting in dual attitudes. Dual attitudes are defined as different evaluations of the same attitude object: an automatic, implicit attitude and an explicit attitude. The attitude that people endorse depends on whether they have the cognitive capacity to retrieve the (...)
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  • Cognitive maps in rats and men.Edward C. Tolman - 1948 - Psychological Review 55 (4):189-208.
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  • Animal Intelligence: Experimental Studies.Edward L. Thorndike - 1912 - Journal of Philosophy, Psychology and Scientific Methods 9 (7):193-194.
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  • On the proper treatment of connectionism.Paul Smolensky - 1988 - Behavioral and Brain Sciences 11 (1):1-23.
    A set of hypotheses is formulated for a connectionist approach to cognitive modeling. These hypotheses are shown to be incompatible with the hypotheses underlying traditional cognitive models. The connectionist models considered are massively parallel numerical computational systems that are a kind of continuous dynamical system. The numerical variables in the system correspond semantically to fine-grained features below the level of the concepts consciously used to describe the task domain. The level of analysis is intermediate between those of symbolic cognitive models (...)
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  • The empirical case for two systems of reasoning.Steven A. Sloman - 1996 - Psychological Bulletin 119 (1):3-22.
    Distinctions have been proposed between systems of reasoning for centuries. This article distills properties shared by many of these distinctions and characterizes the resulting systems in light of recent findings and theoretical developments. One system is associative because its computations reflect similarity structure and relations of temporal contiguity. The other is "rule based" because it operates on symbolic structures that have logical content and variables and because its computations have the properties that are normally assigned to rules. The systems serve (...)
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  • On the generality of the laws of learning.Martin E. Seligman - 1970 - Psychological Review 77 (5):406-418.
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  • Perceptual Pluralism.Jake Quilty-Dunn - 2019 - Noûs 54 (4):807-838.
    Perceptual systems respond to proximal stimuli by forming mental representations of distal stimuli. A central goal for the philosophy of perception is to characterize the representations delivered by perceptual systems. It may be that all perceptual representations are in some way proprietarily perceptual and differ from the representational format of thought (Dretske 1981; Carey 2009; Burge 2010; Block ms.). Or it may instead be that perception and cognition always trade in the same code (Prinz 2002; Pylyshyn 2003). This paper rejects (...)
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  • Furnishing the Mind: Concepts and Their Perceptual Basis.Jesse J. Prinz - 2002 - MIT Press.
  • The propositional nature of human associative learning.Chris J. Mitchell, Jan De Houwer & Peter F. Lovibond - 2009 - Behavioral and Brain Sciences 32 (2):183-198.
    The past 50 years have seen an accumulation of evidence suggesting that associative learning depends on high-level cognitive processes that give rise to propositional knowledge. Yet, many learning theorists maintain a belief in a learning mechanism in which links between mental representations are formed automatically. We characterize and highlight the differences between the propositional and link approaches, and review the relevant empirical evidence. We conclude that learning is the consequence of propositional reasoning processes that cooperate with the unconscious processes involved (...)
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  • Letting structure emerge: connectionist and dynamical systems approaches to cognition.James L. McClelland, Matthew M. Botvinick, David C. Noelle, David C. Plaut, Timothy T. Rogers, Mark S. Seidenberg & Linda B. Smith - 2010 - Trends in Cognitive Sciences 14 (8):348-356.
  • Troubles with Bayesianism: An introduction to the psychological immune system.Eric Mandelbaum - 2018 - Mind and Language 34 (2):141-157.
    A Bayesian mind is, at its core, a rational mind. Bayesianism is thus well-suited to predict and explain mental processes that best exemplify our ability to be rational. However, evidence from belief acquisition and change appears to show that we do not acquire and update information in a Bayesian way. Instead, the principles of belief acquisition and updating seem grounded in maintaining a psychological immune system rather than in approximating a Bayesian processor.
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  • Numerical Architecture.Eric Mandelbaum - 2013 - Topics in Cognitive Science 5 (1):367-386.
    The idea that there is a “Number Sense” (Dehaene, 1997) or “Core Knowledge” of number ensconced in a modular processing system (Carey, 2009) has gained popularity as the study of numerical cognition has matured. However, these claims are generally made with little, if any, detailed examination of which modular properties are instantiated in numerical processing. In this article, I aim to rectify this situation by detailing the modular properties on display in numerical cognitive processing. In the process, I review literature (...)
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  • Against alief.Eric Mandelbaum - 2013 - Philosophical Studies 165 (1):197-211.
    This essay attempts to clarify the nature and structure of aliefs. First I distinguish between a robust notion of aliefs and a deflated one. A robust notion of aliefs would introduce aliefs into our psychological ontology as a hitherto undiscovered kind, whereas a deflated notion of aliefs would identify aliefs as a set of pre-existing psychological states. I then propose the following dilemma: one the one hand, if aliefs have propositional content, then it is unclear exactly how aliefs differ from (...)
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  • Stereotypes, Prejudice, and the Taxonomy of the Implicit Social Mind.Alex Madva & Michael Brownstein - 2018 - Noûs 52 (3):611-644.
    How do cognition and affect interact to produce action? Research in intergroup psychology illuminates this question by investigating the relationship between stereotypes and prejudices about social groups. Yet it is now clear that many social attitudes are implicit. This raises the question: how does the distinction between cognition and affect apply to implicit mental states? An influential view—roughly analogous to a Humean theory of action—is that “implicit stereotypes” and “implicit prejudices” constitute two separate constructs, reflecting different mental processes and neural (...)
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  • On the Systematicity of Language and Thought.Kent Johnson - 2004 - Journal of Philosophy 101 (3):111-139.
  • Connectionism and cognitive architecture: A critical analysis.Jerry A. Fodor & Zenon W. Pylyshyn - 1988 - Cognition 28 (1-2):3-71.
    This paper explores the difference between Connectionist proposals for cognitive a r c h i t e c t u r e a n d t h e s o r t s o f m o d e l s t hat have traditionally been assum e d i n c o g n i t i v e s c i e n c e . W e c l a i m t h a t t h (...)
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  • The Modularity of Mind.Robert Cummins & Jerry Fodor - 1983 - Philosophical Review 94 (1):101.
  • Some reductive strategies in cognitive neurobiology.Paul M. Churchland - 1986 - Mind 95 (July):279-309.
  • Neural representation and neural computation.Patricia Smith Churchland & Terrence J. Sejnowski - 1990 - Philosophical Perspectives 4:343-382.
  • A Neurocomputational Perspective: The Nature of Mind and the Structure of Science.Paul M. Churchland - 1989 - MIT Press.
    A Neurocomputationial Perspective illustrates the fertility of the concepts and data drawn from the study of the brain and of artificial networks that model the...
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  • Rational models of conditioning.Nick Chater - 2009 - Behavioral and Brain Sciences 32 (2):204-205.
    Mitchell et al. argue that conditioning phenomena may be better explained by high-level, rational processes, rather than by non-cognitive associative mechanisms. This commentary argues that this viewpoint is compatible with neuroscientific data, may extend to nonhuman animals, and casts computational models of reinforcement learning in a new light.
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  • Probabilistic models of cognition: Conceptual foundations.Nick Chater & Alan Yuille - 2006 - Trends in Cognitive Sciences 10 (7):287-291.
    Remarkable progress in the mathematics and computer science of probability has led to a revolution in the scope of probabilistic models. In particular, ‘sophisticated’ probabilistic methods apply to structured relational systems such as graphs and grammars, of immediate relevance to the cognitive sciences. This Special Issue outlines progress in this rapidly developing field, which provides a potentially unifying perspective across a wide range of domains and levels of explanation. Here, we introduce the historical and conceptual foundations of the approach, explore (...)
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  • Connectionism and compositionality: Why Fodor and Pylyshyn were wrong.David J. Chalmers - 1993 - Philosophical Psychology 6 (3):305-319.
    This paper offers both a theoretical and an experimental perspective on the relationship between connectionist and Classical (symbol-processing) models. Firstly, a serious flaw in Fodor and Pylyshyn’s argument against connectionism is pointed out: if, in fact, a part of their argument is valid, then it establishes a conclusion quite different from that which they intend, a conclusion which is demonstrably false. The source of this flaw is traced to an underestimation of the differences between localist and distributed representation. It has (...)
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  • Implicit attitudes and awareness.Jacob Berger - 2020 - Synthese 197 (3):1291-1312.
    I offer here a new hypothesis about the nature of implicit attitudes. Psy- chologists and philosophers alike often distinguish implicit from explicit attitudes by maintaining that we are aware of the latter, but not aware of the former. Recent experimental evidence, however, seems to challenge this account. It would seem, for example, that participants are frequently quite adept at predicting their own perfor- mances on measures of implicit attitudes. I propose here that most theorists in this area have nonetheless overlooked (...)
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  • Language of thought: The connectionist contribution.Murat Aydede - 1997 - Minds and Machines 7 (1):57-101.
    Fodor and Pylyshyn's critique of connectionism has posed a challenge to connectionists: Adequately explain such nomological regularities as systematicity and productivity without postulating a "language of thought" (LOT). Some connectionists like Smolensky took the challenge very seriously, and attempted to meet it by developing models that were supposed to be non-classical. At the core of these attempts lies the claim that connectionist models can provide a representational system with a combinatorial syntax and processes sensitive to syntactic structure. They are not (...)
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  • An Essay Concerning Human Understanding. To Which Are Now Added, I. Analysis of Mr. Locke's Doctrine of Ideas [&C.].John Locke - 1818
  • Categorization and Naming in Children: Problems of Induction.Ellen M. Markman - 1989 - MIT Press.
    In this landmark work on early conceptual and lexical development, Ellen Markman explores the fascinating problem of how young children succeed at the task of ...
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  • A treatise of human nature.David Hume - 1739 - In Elizabeth Schmidt Radcliffe, Richard McCarty, Fritz Allhoff & Anand Vaidya (eds.), Late modern philosophy: essential readings with commentary. Wiley-Blackwell.
  • Measuring Individual Differences in Implicit Cognition: The Implicit Association Test.Debbie E. McGhee, Jordan L. K. Schwartz & Anthony G. Greenwald - 1998 - Journal of Personality and Social Psychology 74 (6):1464-1480.
    An implicit association test (IAT) measures differential association of 2 target concepts with an attribute. The 2 concepts appear in a 2-choice task (e.g., flower vs. insect names), and the attribute in a 2nd task (e.g., pleasant vs. unpleasant words for an evaluation attribute). When instructions oblige highly associated categories (e.g., flower + pleasant) to share a response key, performance is faster than when less associated categories (e.g., insect + pleasant) share a key. This performance difference implicitly measures differential association (...)
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  • What Might Cognition Be, If Not Computation?Tim Van Gelder - 1995 - Journal of Philosophy 92 (7):345 - 381.
  • Hard Words.Lila R. Gleitman, Anna Papafragou & John C. Trueswell - unknown
    How do children acquire the meaning of words? And why are words such as know harder for learners to acquire than words such as dog or jump? We suggest that the chief limiting factor in acquiring the vocabulary of natural languages consists not in overcoming conceptual difficulties with abstract word meanings but rather in mapping these meanings onto their corresponding lexical forms. This opening premise of our position, while controversial, is shared with some prior approaches. The present discussion moves forward (...)
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  • Moving from Levels & Reduction to Dimensions & Constraints.David Danks - unknown
    Arguments, claims, and discussions about the “level of description” of a theory are ubiquitous in cognitive science. Such talk is typically expressed more precisely in terms of the granularity of the theory, or in terms of Marr’s three levels. I argue that these ways of understanding levels of description are insufficient to capture the range of different types of theoretical commitments that one can have in cognitive science. When we understand these commitments as points in a multi-dimensional space, we find (...)
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  • Hume Variations.Jerry A. Fodor - 2003 - Revue Philosophique de la France Et de l'Etranger 195 (2):243-244.
     
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  • Systems and Levels: Dual System Theories and the Personal-Subpersonal Distinction, in: J.Keith Frankish - 2009 - In Jonathan Evans & Keith Frankish (eds.), In Two Minds: Dual Processes and Beyond. Oxford University Press.
    About the book: This book explores the idea that we have two minds - automatic, unconscious, and fast, the other controlled, conscious, and slow. In recent years there has been great interest in so-called dual-process theories of reasoning and rationality. According to such theories, there are two distinct systems underlying human reasoning - an evolutionarily old system that is associative, automatic, unconscious, parallel, and fast, and a more recent, distinctively human system that is rule-based, controlled, conscious, serial, and slow. Within (...)
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  • Critique of Pure Reason.I. Kant - 1787/1998 - Philosophy 59 (230):555-557.
  • The Principles of Psychology.William James - 1890 - Les Etudes Philosophiques 11 (3):506-507.
     
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  • Steps Toward Artificial Intelligence.Marvin Minsky - unknown
    Received by the IRE, October 24, 1960. The author's work summarized here—which was done at the MIT Lincoln Laboratory, a center for research operated by MIT at Lexington, Mass., with the joint Support of the U. S. Army, Navy, and Air Force under Air Force Contract AF 19-5200; and at the Res. Lab. of Electronics, MIT, Cambridge, Mass., which is supported in part by the U. S. Army Signal Corps, the Air Force Office of Scientific Research, and the ONR—is based (...)
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  • Conditioned Reflexes.I. P. Pavlov - 1927 - Les Etudes Philosophiques 17 (4):560-560.
     
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  • Putting Concepts to Work: Some Thoughts for the 21st Century.Andy Clark & Jesse Prinz - unknown
    Fodor’s theory makes thinking prior to doing. It allows for an inactive agent or pure reflector, and for agents whose actions in various ways seem to float free of their own conceptual repertoires. We show that naturally evolved creatures are not like that. In the real world, thinking is always and everywhere about doing. The point of having a brain is to guide the actions of embodied beings in a complex material world. Some of those actions are, to be sure, (...)
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  • Science and human behavior.B. F. Skinner - 1954 - Revue Philosophique de la France Et de l'Etranger 144:268-269.
     
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  • The Number Sense: How the Mind Creates Mathematics.Stanislas Dehaene - 1999 - British Journal of Educational Studies 47 (2):201-203.
  • The continuity of levels of nature.William G. Lycan - 1990 - In Mind and Cognition: A Reader. Blackwell. pp. 77--96.