This paper describes a theory that explains both the creativity and the efficiency of people's conceptual combination. In the constraint theory, conceptual combination is controlled by three constraints of diagnosticity, plausibility, and informativeness. The constraints derive from the pragmatics of communication as applied to compound phrases. The creativity of combination arises because the constraints can be satisfied in many different ways. The constraint theory yields an algorithmic model of the efficiency of combination. The C3 model admits the full creativity of (...) combination and yet efficiently settles on the best interpretation for a given phrase. The constraint theory explains many empirical regularities in conceptual combination, and makes various empirically verified predictions. In computer simulations of compound phrase interpretation, the C3 model has produced results in general agreement with people's responses to the same phrases. (shrink)

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.

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 (...) complementary functions and can simultaneously generate different solutions to a reasoning problem. The rule-based system can suppress the associative system but not completely inhibit it. The article reviews evidence in favor of the distinction and its characterization. (shrink)

I examine the phenomenon of implicit learning, the process by which knowledge about the rule-governed complexities of the stimulus environment is acquired independently of conscious attempts to do so. Our research with the two seemingly disparate experimental paradigms of synthetic grammar learning and probability learning, is reviewed and integrated with other approaches to the general problem of unconscious cognition. The conclusions reached are as follows: Implicit learning produces a tacit knowledge base that is abstract and representative of the structure of (...) the environment; such knowledge is optimally acquired independently of conscious efforts to learn; and it can be used implicitly to solve problems and make accurate decisions about novel stimulus circumstances. Various epistemological issues and related problems such as intuition, neuroclinical disorders of learning and memory, and the relationship of evolutionary processes to cognitive science are also discussed. (shrink)

Over the last quarter century, the dominant tendency in comparative cognitive psychology has been to emphasize the similarities between human and nonhuman minds and to downplay the differences as (Darwin 1871). In the present target article, we argue that Darwin was mistaken: the profound biological continuity between human and nonhuman animals masks an equally profound discontinuity between human and nonhuman minds. To wit, there is a significant discontinuity in the degree to which human and nonhuman animals are able to approximate (...) the higher-order, systematic, relational capabilities of a physical symbol system (PSS) (Newell 1980). We show that this symbolic-relational discontinuity pervades nearly every domain of cognition and runs much deeper than even the spectacular scaffolding provided by language or culture alone can explain. We propose a representational-level specification as to where human and nonhuman animals' abilities to approximate a PSS are similar and where they differ. We conclude by suggesting that recent symbolic-connectionist models of cognition shed new light on the mechanisms that underlie the gap between human and nonhuman minds. (shrink)

One of the main challenges that Jerry Fodor and Zenon Pylyshyn (Cognition 28:3–71, 1988) posed for any connectionist theory of cognitive architecture is to explain the systematicity of thought without implementing a Language of Thought (LOT) architecture. The systematicity challenge presents a dilemma: if connectionism cannot explain the systematicity of thought, then it fails to offer an adequate theory of cognitive architecture; and if it explains the systematicity of thought by implementing a LOT architecture, then it fails to offer an (...) alternative to the LOT hypothesis. Given that thought is systematic, connectionism can offer an adequate alternative to the LOT hypothesis only if it can meet the challenge. Although some critics tried to meet the challenge, others argued that it need not be met since thought is not in fact systematic; and some claimed not to even understand the claim that thought is systematic. I do not here examine attempts to answer the challenge. Instead, I defend the challenge itself by explicating the notion of systematicity in a way that I hope makes clear that thought is indeed systematic, and so that to offer an adequate alternative to the LOT hypothesis, connectionism must meet the challenge. (shrink)

Fodor's and Pylyshyn's stand on systematicity in thought and language has been debated and criticized. Van Gelder and Niklasson, among others, have argued that Fodor and Pylyshyn offer no precise definition of systematicity. However, our concern here is with a learning based formulation of that concept. In particular, Hadley has proposed that a network exhibits strong semantic systematicity when, as a result of training, it can assign appropriate meaning representations to novel sentences (both simple and embedded) which contain words in (...) syntactic positions they did not occupy during training. The experience of researchers indicates that strong systematicity in any form is difficult to achieve in connectionist systems.Herein we describe a network which displays strong semantic systematicity in response to Hebbian, connectionist training. During training, two-thirds of all nouns are presented only in a single syntactic position (either as grammatical subject or object). Yet, during testing, the network correctly interprets thousands of sentences containing those nouns in novel positions. In addition, the network generalizes to novel levels of embedding. Successful training requires a, corpus of about 1000 sentences, and network training is quite rapid. The architecture and learning algorithms are purely connectionist, but classical insights are discernible in one respect, viz, that complex semantic representations spatially contain their semantic constituents. However, in other important respects, the architecture is distinctly non-classical. (shrink)

Fodor's and Pylyshyn's stand on systematicity in thought and language has been debated and criticized. Van Gelder and Niklasson, among others, have argued that Fodor and Pylyshyn offer no precise definition of systematicity. However, our concern here is with a learning based formulation of that concept. In particular, Hadley has proposed that a network exhibits strong semantic systematicity when, as a result of training, it can assign appropriate meaning representations to novel sentences (both simple and embedded) which contain words in (...) syntactic positions they did not occupy during training. The experience of researchers indicates that strong systematicity in any form is difficult to achieve in connectionist systems.Herein we describe a network which displays strong semantic systematicity in response to Hebbian, connectionist training. During training, two-thirds of all nouns are presented only in a single syntactic position (either as grammatical subject or object). Yet, during testing, the network correctly interprets thousands of sentences containing those nouns in novel positions. In addition, the network generalizes to novel levels of embedding. Successful training requires a, corpus of about 1000 sentences, and network training is quite rapid. The architecture and learning algorithms are purely connectionist, but ‘classical’ insights are discernible in one respect, viz, that complex semantic representations spatially contain their semantic constituents. However, in other important respects, the architecture is distinctly non-classical. (shrink)

This is a review of Mind and Supermind. By KEITH FRANKISH. (Cambridge: Cambridge University Press, 2004. Pp xiv + 255. Price £45.00 (US $75.00). ISBN 0521 812038 (hardback).

Mind and Supermind offers an alternative perspective on the nature of belief and the structure of the human mind. Keith Frankish argues that the folk-psychological term 'belief' refers to two distinct types of mental state, which have different properties and support different kinds of mental explanation. Building on this claim, he develops a picture of the human mind as a two-level structure, consisting of a basic mind and a supermind, and shows how the resulting account sheds light on a number (...) of puzzling phenomena and helps to vindicate folk psychology. Topics discussed include the function of conscious thought, the cognitive role of natural language, the relation between partial and flat-out belief, the possibility of active belief formation, and the nature of akrasia, self-deception and first-person authority. This book will be valuable for philosophers, psychologists and cognitive scientists. (shrink)

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 (...) e m a j o r d i s t i n c t i o n i s t h a t , w h i l e b o t h Connectionist and Classical architectures postulate representational mental states, the latter but not the former are committed to a symbol-level of representation, or to a ‘language of thought’: i.e., to representational states that have combinatorial syntactic and semantic structure. Several arguments for combinatorial structure in mental representations are then reviewed. These include arguments based on the ‘systematicity’ of mental representation: i.e., on the fact that cognitive capacities always exhibit certain symmetries, so that the ability to entertain a given thought implies the ability to entertain thoughts with semantically related contents. We claim that such arguments make a powerful case that mind/brain architecture is not Connectionist at the cognitive level. We then consider the possibility that Connectionism may provide an account of the neural (or ‘abstract neurological’) structures in which Classical cognitive architecture is implemented. We survey a n u m b e r o f t h e s t a n d a r d a r g u m e n t s t h a t h a v e b e e n o f f e r e d i n f a v o r o f Connectionism, and conclude that they are coherent only on this interpretation. (shrink)

The renowned philosopher Jerry Fodor, a leading figure in the study of the mind for more than twenty years, presents a strikingly original theory on the basic constituents of thought. He suggests that the heart of cognitive science is its theory of concepts, and that cognitive scientists have gone badly wrong in many areas because their assumptions about concepts have been mistaken. Fodor argues compellingly for an atomistic theory of concepts, deals out witty and pugnacious demolitions of rival theories, and (...) suggests that future work on human cognition should build upon new foundations. This lively, conversational, and superbly accessible book is the first volume in the Oxford Cognitive Science Series, where the best original work in this field will be presented to a broad readership. Concepts will fascinate anyone interested in contemporary work on mind and language. Cognitive science will never be the same again. (shrink)

The implicit-explicit distinction is applied to knowledge representations. Knowledge is taken to be an attitude towards a proposition which is true. The proposition itself predicates a property to some entity. A number of ways in which knowledge can be implicit or explicit emerge. If a higher aspect is known explicitly then each lower one must also be known explicitly. This partial hierarchy reduces the number of ways in which knowledge can be explicit. In the most important type of implicit knowledge, (...) representations merely reflect the property of objects or events without predicating them of any particular entity The dearest cases of explicit knowledge of a fact are representations of one's own attitude of knowing that fact. These distinctions are discussed in their relationship to similar distinctions such as procedural-declarative, conscious unconscious, verbalizable-nonverbalizable, direct-indirect tests, and automatic voluntary control. This is followed by an outline of how these distinctions can be used to integrate and relate the often divergent uses of the implicit-explicit distinction in different research areas. We illustrate this for visual perception, memory, cognitive development, and artificial grammar learning. (shrink)

Jerry Fodor presents a new development of his famous Language of Thought hypothesis, which has since the 1970s been at the centre of interdisciplinary debate about how the mind works. Fodor defends and extends the groundbreaking idea that thinking is couched in a symbolic system realized in the brain. This idea is central to the representational theory of mind which Fodor has established as a key reference point in modern philosophy, psychology, and cognitive science. The foundation stone of our present (...) cognitive science is Turing's suggestion that cognitive processes are not associations but computations; and computation requires a language of thought. So the latest on the Language of Thought hypothesis, from its progenitor, promises to be a landmark in the study of the mind. LOT 2 offers a more cogent presentation and a fuller explication of Fodor 's distinctive account of the mind, with various intriguing new features. The central role of compositionality in the representational theory of mind is revealed: most of what we know about concepts follows from the compositionality of thoughts. Fodor shows the necessity of a referentialist account of the content of intentional states, and of an atomistic account of the individuation of concepts. Not least among the new developments is Fodor 's identification and persecution of pragmatism as the leading source of error in the study of the mind today. LOT 2 sees Fodor advance undaunted towards the ultimate goal of a theory of the cognitive mind, and in particular a theory of the intentionality of cognition. No one who works on the mind can ignore Fodor 's views, expressed in the coruscating and provocative style which has delighted and disconcerted countless readers over the years. (shrink)

The idea that the language we speak influences the way we think has evoked perennial fascination and intense controversy. According to the strong version of this hypothesis, called the Sapir-Whorf hypothesis after the American linguists who propounded it, languages vary in their semantic partitioning of the world, and the structure of one’s language influences how one understands the world. Thus speakers of different languages perceive the world differently. Although the last two decades have been marked by extreme skepticism concerning the (...) possible effects of language on thought, recent theoretical and methodological advances in cognitive science have given the question new life. Research in linguistics and linguistic anthropology has revealed striking differences in cross-linguistic semantic patterns, and cognitive psychology has developed subtle techniques for studying how people represent and remember experience. It is now possible to test predictions about how a given language influences the thinking of its speakers. Language in Mind includes contributions from both skeptics and believers and from a range of fields. It contains work in cognitive psychology, cognitive development, linguistics, anthropology, and animal cognition. The topics discussed include space, number, motion, gender, theory of mind, thematic roles, and the ontological distinction between objects and substances. I Introduction 1 Whither Whorf 3 Dedre Gentner and Susan Goldin-Meadow II Position Statements 15 1 Languages and Representations 17 Eve V. Clark 2 Language and Mind: Let’s Get the Issues Straight! 25 Stephen C. Levinson 3 The Key Is Social Cognition 47 Michael Tomasello III Language as Lens: Does the Language We Acquire Influence How We See the World? 59 4 Sex, Syntax, and Semantics 61 Lera Boroditsky, Lauren A. Schmidt, and Webb Phillips 5 Speaking versus Thinking about Objects and Actions 81 Barbara C. Malt, Steven A. Sloman, and Silvia P. Gennari 6 The Effects of Spatial Language on Spatial Representation: Setting Some Boundaries 113 Edward Munnich and Barbara Landau 7 Language and Thought Online: Cognitive Consequences of Linguistic Relativity 157 Dan I. Slobin IV Language as Tool Kit: Does the Language We Acquire Augment Our Capacity for Higher-Order Representation and Reasoning? 193 8 Why We’re So Smart 195 Dedre Gentner 9 Does Language Help Animals Think? 237 Stan A. Kuczaj, II, and Jennifer L. Hendry 10 What Makes Us Smart? Core Knowledge and Natural Language 277 Elizabeth S. Spelke 11 Conceptual and Linguistic Factors in Inductive Projection: How Do Young Children Recognize Commonalities between Animals and Plants? 313 Kayoko Inagaki and Giyoo Hatano 12 Language for Thought: Coming to Understand False Beliefs 335 Jill G. de Villiers and Peter A. de Villiers V Language as Category Maker: Does the Language We Acquire Influence Where We Make Our Category Distinctions? 385 13 Space under Construction: Language-Specific Spatial Categorization in First Language Acquisition 387 Melissa Bowerman and Soonja Choi 14 Reevaluating Linguistic Relativity: Language-Specific Categories and the Role of Universal Ontological Knowledge in the Construal of Individuation 429 Mutsumi Imai and Reiko Mazuka 15 Interaction of Language Type and Referent Type in the Development of Nonverbal Classification Preferences 465 John A. Lucy and Suzanne Gaskins 16 Thought before Language: Do We Think Ergative? 493 Susan Goldin-Meadow. (shrink)

The Systematicity Arguments is the only book-length treatment of the systematicity and productivity arguments.

This book presents an overview of these studies and attempts to clarify apparently disparate results by placing them in a coherent theoretical framework.

Je lui ai associÉ un court extrait d'une revue de questions portant sur le même thème. Implicit memory is revealed when previous experiences facilitate perf on a task that does not require conscious or intentional recollection of those expces. Explicit memory is revealed when perf on a task requires conscious recolelction of previous expces. Il s'agit de defs descriptives qui n'impliquent pas l'existence de deux systs de mÉmo sÉparÉs. Historiquement Descartes est le premier ˆ faire mention de phÉnomènes de mÉmo (...) implicites, Leibniz, Maine de Biran, Bergson en ont Également parlÉ. Korsakoff (1889) avec ses travaux sur les amnÉsiques montre qu'ils sont capables d'utiliser de l'info qu'ils ont acquises dans des Épisodes rÉcents sans pour autant manifester le moindre souvenir de l'Épisode. L'interprÉtation de ces phÉnomènes Était alors que ça renvoyait ˆ des traces en mÉmoire trop tÉnues pour accèder jusqu'au champ de la conscience. Cette interprÉtation va pouvoir être ÉcartÉe par les travaux rÉcents. Thorndike a Également conduit un nbre important de travaux sur MI. Les trauvaux un peu plus rÉcents ont montrÉ qu'un apprentissage antÉrieur pouvait faciliter une perfce sans qu'il y ait ref explicite à l'Épisode d'apprentissage. On a montrÉ aussi l'effet de stimuli subliminaux, qui en tant que tels ne peuvent pas être rappelÉs consciemment, mais qui influencent la conduite ou les jugts ultÉrieurs. Par ex, la prÉsentation de formes sur des temps très courts qui excluent la possibilitÉ d'une perception consciente influence significativement lechoix de formes dans une pÉreuve ultÉrieure de choix forcÉs où les sjts doivent indiquer la forme qu'il prÉfère entre deux. Ils choisissent prÉfÉrentiellement celles qui leur ont ÉtÉ prÉsentÉes de manière subliminale. De même Bargh et al. ont montrÉ que des sjts soumis de manière subliminale ˆ des mots hostiles portent ultÉrieurement des jugts plus nÉgatifs sur une personne target. Il ya Également eu des travaux sur l'apprsge ou le condt without awareness en particulier apprsge implicite de règles de grammaire (ie le sjt peut construire de nouvelles phrases conformes ˆ la syntaxe de celles qui lui ont ÉtÉ prÉsentÉes sans pour autant petre capables d'noncer les règles de grammaire qu'il utilise) Rem: N'est ce pas un pbe de typemÉtacognition??? Enfin, tous les travaux sur le priming sont des elts en faveur de MI: Facilitation in the processing of a stimulus as a function of a recent encounter with the same stimulus. Type de perfce sur lesquels les effets de priming ont ÉtÉ dÉmontrÉs: -T‰ches de dÉcision lexicale: Le sjt doit dire si la cha"ne de caractères qu'on lui prÉsente est un mot ou pas: Le temps de latence est beaucoup plus court si la cha"ne a dÉjˆ ÉtÉ prÉsentÉe une première fois. -Mesures de temps d'identification de mots en rpÉsentation tachitoscopiques -ComplÉmentation de mots: les sjts ont tendance ˆ complÉter pour crÉer les mots qui leur ont ÉtÉ prÉsentÉs antÉrieurement. L'intÉrêt pour le paradigme de priming se retouve chez les gens qui s'intÉressent ˆ: -reconnaissance de mots et organisation lexicale. les effets de priming permettent de faire des hyps sur l'accès lexical et la reprÉsentation. -M. Épisodique: travux sur les amnÉsiques qui ne se souviennent pas qu'on vient de leur prÉsenter des mots mais qui manifestent une mÉmoire implicite lorsqu'on leur fait faire de la complÉmentation de mots. DISSOCIATION ENTRE M.I. ET M EXPLICITE 1-Si de nombreux travaux montrent que la M explicite est influencÉe par le travail d'Élaboration (profondeur de traitement) en jeu pendant la première phase d'Étude des stimuli, il semble que la MI ne le soit pas. 2-Le changt de modalitÉ (par ex auditif -> visuel) entre la phase d'Étude et la phase de test provoque une attÉnuation importante de l'effet de priming si le test est un test de MI mais pas si c'est un test de ME. 3-Les effets de primings persistent assez largement sur plusieurs jours ce qui n'est pas le cas des perfces ˆ une Épreuve de reconnaissance. 4-Les perfces sur des tests de MI ne semblent pas influencÉes par des manipulations d'interfÉrences proactives ou rÉtroactives dont on sait qu'elles influencent les perfces en ME. 5-Absce de corrÉlation entre perfces ˆ des tests de reconnaissance et perfces ˆ une Épreuve de complÉmentation de mots. SIMILARITES ENTRE PRIMING ET REMEMBERING 1- A certaines conditions les durÉes de rÉtention on des effets parallèles sur les effets de priming et les mesures de ME (REm: en partie contradictoire avec 3 ci dessus) 2-La manipulation du contexte de la liste lors de la phase d'Étude affecte ˆ la fois les perfces en reconnaissance et en identification de mots. 3- ME et MI sont influencÉes par des associations nouvellement acquises entre des paires de mots non reliÉes (Rem: contradictoires avec 4 ci dessus ??) 4- Rem: Le contraire de 1 du pt "dissociation" !!!! dans une manip particulière 5-Johnston et al. ont montrÉ que des mots identifÉs plus rapidement Étaient plus svt jugÉs comme 'old' dans une t‰che de reconnaissance que les mots identifiÉs plus lentement. Il n'est pas exclu que les phÉnomènes que l'on interprètent comme relevant de MI soient parfois de la ME involontaire cad des cas o les cues fournis dans le test conduisent ˆ un souvenir involontaire mais totalement conscient. LES INTERPRETATIONS THEORIQUES DE MI 1-Les effets de priming sur des test de MI sont attribuables ˆ l'activation temporaires de reprÉsentations ou structures de K prÉ-existantes . Cette activation est supposÉe avoir lieu de manière automatique, indÉpendamment des processus d'Élaboration nÉcessaires pour Établir de nouvelles traces Épisodiques. 2- les difÉrences entre ME et MI sont dues ˆ la nature et aux relations entre les processus d'encodage et de rÉcupÉration. Une version de cette approche est celle qui s'appuie sur la distinction entre processus dirigÉs par les donnÉes et processus dirigÉs par les concepts. Ces derniers reflètent des activitÉs initiÉes par le sjt comme l'Élaboration, l'organisation et la reconstruction, c'est sur ce type de processus que reposerait la ME alors que la MI reposerait sur des processus data-driven. 3-ME et MI renvoient ˆ des systs sous jacents diffÉrents. Pour Cohen & Squire (1984), la ME est supportÉe par une M DECLARATIVE , syst qui est en jeu dans la formation de nouvelles reprÉsentations. La MI repose sur un syst PROCEDURAL dans lequel la M se manifeste par des modifications on line de procÉdures ou opÉrations de traitement. Le syst de M Épisodique est vu comme la base pour le souvenir explicite d'evts rÉcents tandis que la M sÉmantique est responsable des perfces sur des tests de MI. Chacune de ces approches est conforme ˆ certaines des donnÉes recueillies mais pas ˆ d'autres. (shrink)