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Beyond modularityattempts a synthesis of Fodor's anticonstructivist nativism and Piaget's antinativist constructivism. Contra Fodor, I argue that: (1) the study of cognitive development is essential to cognitive science, (2) the module/central processing dichotomy is too rigid, and (3) the mind does not begin with prespecified modules; rather, development involves a gradual process of “modularization.” Contra Piaget, I argue that: (1) development rarely involves stagelike domain-general change and (2) domainspecific predispositions give development a small but significant kickstart by focusing the infant's (...) attention on proprietary inputs. Development does not stop at efficient learning. A fundamental aspect of human development (“representational redescription”) is the hypothesized process by which information that isina cognitive system becomes progressively explicit knowledgetothat system. Development thus involves two complementary processes of progressive modularization and progressive “explicitation.” Empirical findings on the child as linguist, physicist, mathematician, psychologist, and notator are discussed in support of the theoretical framework. Each chapter concentrates first on the initial state of the infant mind/brain and on subsequent domain-specific learning in infancy and early childhood. It then goes on to explore data on older children's problem solving and theory building, with particular focus on evolving cognitive flexibility. Emphasis is placed throughout on the status of representations underlying different capacities and on the multiple levels at which knowledge is stored and accessible. Finally, consideration is given to the need for more formal developmental models, and a comparison is made between representational redescription and connectionist simulations of development. In conclusion, I consider what is special about human cognition by speculating on the status of representations underlying the structure of behavior in other species. (shrink) | |
During the first two years of human life a common neural substrate underlies the hierarchical organization of elements in the development of speech as well as the capacity to combine objects manually, including tool use. Subsequent cortical differentiation, beginning at age two, creates distinct, relatively modularized capacities for linguistic grammar and more complex combination of objects. An evolutionary homologue of the neural substrate for language production and manual action is hypothesized to have provided a foundation for the evolution of language (...) before the divergence of the hominids and the great apes. Support comes from the discovery of a Broca's area homologue and related neural circuits in contemporary primates. In addition, chimpanzees have an identical constraint on hierarchical complexity in both tool use and symbol combination. Their performance matches that of the two-year-old child who has not yet developed the neural circuits for complex grammar and complex manual combination of objects. (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) | |
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A fundamental goal of linguistic theory is to explain how natural languages are acquired. This paper describes some recent findings on how learners acquire syntactic knowledge for which there is little, if any, decisive evidence from the environment. The first section presents several general observations about language acquisition that linguistic theory has tried to explain and discusses the thesis that certain linguistic properties are innate because they appear universally and in the absence of corresponding experience. A third diagnostic for innateness, (...) early emergence, is the focus of the second section of the paper, in which linguistic theory is tested against recent experimental evidence on children's acquisition of syntax. (shrink) | |
The human species is more reliant on cultural adaptation than any other species, but it is unclear how observational learning can give rise to the faithful transmission of cultural adaptations. One possibility is that teaching facilitates accurate social transmission by narrowing the range of inferences that learners make. However, there is wide disagreement about how to define teaching, and how to interpret the empirical evidence for teaching across cultures and species. In this article I argue that disputes about the nature (...) and prevalence of teaching across human societies and nonhuman animals are based on a number of deep-rooted theoretical differences between fields, as well as on important differences in how teaching is defined. To reconcile these disparate bodies of research, I review the three major approaches to the study of teaching – mentalistic, culture-based, and functionalist – and outline the research questions about teaching that each addresses. I then argue for a new, integrated framework that differentiates between teaching types according to the specific adaptive problems that each type solves, and apply this framework to restructure current empirical evidence on teaching in humans and nonhuman animals. This integrative framework generates novel insights, with broad implications for the study of the evolution of teaching, including the roles of cognitive constraints and cooperative dilemmas in how and when teaching evolves. Finally, I propose an explanation for why some types of teaching are uniquely human, and discuss new directions for research motivated by this framework. (shrink) | |
Two central assumptions of current models of language acquisition were addressed in this study: (1) knowledge of linguistic structure is "mapped onto" earlier forms of non-linguistic knowledge; and (2) acquiring a language involves a continuous learning sequence from early gestural communication to linguistic expression. The acquisition of the first and second person pronouns ME and YOU was investigated in a longitudinal study of two deaf children of deaf parents learning American Sign Language (ASL) as a first language. Personal pronouns in (...) ASL are formed by pointing directly to the addressee (YOU) or self (I or ME), rather than by arbitrary symbols. Thus, personal pronouns in ASL resemble paralinguistic gestures that commonly accompany speech and are used prelinguistically by both hearing and deaf children beginning around 9 months. This provides a means for investigating the transition from prelinguistic gestural to linguistic expression when both gesture and language reside in the same modality.\nThe results indicate that deaf children acquired knowledge of personal pronouns over a period of time, displaying errors similar to those of hearing children despite the transparency of the pointing gestures. The children initially (ages 10 and 12 months) pointed to persons, objects, and locations. Both children then exhibited a long avoidance period, during which one function of the pointing gesture (pointing to self and others) dropped out completely. During this period their language and cognitive development were otherwise entirely normal, and they continued to use other types of pointing (e.g., to objects). When pointing to self and others returned, it was marked with errors typical of hearing children; one child exhibited consistent pronoun reversal errors, thinking the YOU point referred to herself, while the other child exhibited reversal errors inconsistently. Evidence from experimental tasks conducted with the first child revealed that pronoun errors occurred in comprehension as well. Full control of the ME and YOU pronouns was not achieved until 25-27 months, around the same time when hearing children master these forms. Thus, the study provides evidence for a discontinuity in the child's transition from prelinguistic to linguistic communication. It is argued that aspects of linguistic structure and its acquisition appear to involve distinct, language-specific knowledge. (shrink) | |
At least since Augustine, philosophers have constructed developmental just-so stories about the origins of certain concepts. In these just-so stories, philosophers tell us how children must develop these concepts. However, philosophers have by and large neglected the empirical data about how children actually do develop their ideas about the world. At best they have used information about children in an anecdotal and unsystematic, though often illuminating, way. | |
This article explicates the interaction between implicit and explicit processes in skill learning, in contrast to the tendency of researchers to study each type in isolation. It highlights various effects of the interaction on learning (including synergy effects). The authors argue for an integrated model of skill learning that takes into account both implicit and explicit processes. Moreover, they argue for a bottom-up approach (first learning implicit knowledge and then explicit knowledge) in the integrated model. A variety of qualitative data (...) can be accounted for by the approach. A computational model, CLARION, is then used to simulate a range of quantitative data. The results demonstrate the plausibility of the model, which provides a new perspective on skill learning. (PsycINFO Database Record (c) 2012 APA, all rights reserved). (shrink) | |
The “puzzle” of emotional plasticity concerns making sense of two conflicting bodies of evidence: evidence that emotions often appear modular in key respects, and evidence that our emotions also often appear to transcend this modularity. In this paper, I argue a developmentalist approach to emotion, which builds on Karmiloff-Smith’s (1986, 1992, 1994, 2015) work on cognitive development, can help us dissolve this puzzle. | |
This paper presents a skill learning model CLARION. Different from existing models of mostly high-level skill learning that use a top-down approach (that is, turning declarative knowledge into procedural knowledge through practice), we adopt a bottom-up approach toward low-level skill learning, where procedural knowledge develops first and declarative knowledge develops later. Our model is formed by integrating connectionist, reinforcement, and symbolic learning methods to perform on-line reactive learning. It adopts a two-level dual-representation framework (Sun, 1995), with a combination of localist (...) and distributed representation. We compare the model with human data in a minefield navigation task, demonstrating some match between the model and human data in several respects. (shrink) | |
Spontaneous tool use and sensorimotor intelligence in Cebus were observed to determine whether tool use is discovered fortuitously and learned by trial-and-error or, rather, whether advanced sensorimotor abilities (experimentation and insight) are critical in its ontogeny and evolution. | |
Like the information patterns that evolve through. biological processes, mental representations or memes evolve through adaptive exploration and transformation of an information space through variation, selection, and transmission. However since memes do not contain instructions for their replication our brains do it for them, strategically, guided by a fitness landscape that reflects both internal drives and a worldview that forms through meme assimilation. This paper presents a tentative model for how an individual becomes a meme evolving agent via the emergence (...) of an autocatalytic network of sparse, distributed memories, and discusses implications for complex creative thought processes and why they are unique to humans. A hypothetical scenario for the evolutionary dynamics of a given meme in a society of interacting individuals is presented. (shrink) No categories | |
A standard view of reference holds that a speaker's use of a name refers to a certain thing in virtue of the speaker's associating a condition with that use that singles the referent out. This view has been criticized by Saul Kripke as empirically inadequate. Recently, however, it has been argued that a version of the standard view, a /response-based theory of reference/, survives the charge of empirical inadequacy by allowing that associated conditions may be largely or even entirely implicit. (...) This paper argues that response-based theories of reference are prey to a variant of the empirical inadequacy objection, because they are ill-suited to accommodate the successful use of proper names by pre-school children. Further, I argue that there is reason to believe that normal adults are, by and large, no different from children with respect to how the referents of their names are determined. I conclude that speakers typically refer /positionally/: the referent of a use of a proper name is typically determined by aspects of the speaker's position, rather than by associated conditions present, however implicitly, in her psychology. (shrink) | |
This paper argues for an explanation of the mechanistic (computational) basis of consciousness that is based on the distinction between localist (symbolic) representation and distributed representation, the ideas of which have been put forth in the connectionist literature. A model is developed to substantiate and test this approach. The paper also explores the issue of the functional roles of consciousness, in relation to the proposed mechanistic explanation of consciousness. The model, embodying the representational difference, is able to account for the (...) functional role of consciousness, in the form of the synergy between the conscious and the unconscious. The fit between the model and various cognitive phenomena and data (documented in the psychological literatures) is discussed to accentuate the plausibility of the model and its explanation of consciousness. Comparisons with existing models of consciousness are made in the end. (shrink) | |
This article addresses issues in developing cognitive architectures--generic computational models of cognition. Cognitive architectures are believed to be essential in advancing understanding of the mind, and therefore, developing cognitive architectures is an extremely important enterprise in cognitive science. The article proposes a set of essential desiderata for developing cognitive architectures. It then moves on to discuss in detail some of these desiderata and their associated concepts and ideas relevant to developing better cognitive architectures. It argues for the importance of taking (...) into full consideration these desiderata in developing future architectures that are more cognitively and ecologically realistic. A brief and preliminary evaluation of existing cognitive architectures is attempted on the basis of these ideas. (shrink) | |
This paper compares two theories and their two corresponding computational models of human moral judgment. In order to better address psychological realism and generality of theories of moral judgment, more detailed and more psychologically nuanced models are needed. In particular, a motivationally based theory of moral judgment is developed in this paper that provides a more accurate account of human moral judgment than an existing emotion-reason conflict theory. Simulations based on the theory capture and explain a range of relevant human (...) data. They account not only for the original data that were used to support the emotion–reason conflict theory, but also for a wider range of data and phenomena. (shrink) | |
_role, especially in learning, and through devising hybrid neural network models that (in a qualitative manner) approxi-_ _mate characteristics of human consciousness. In doing so, the paper examines explicit and implicit learning in a variety_ _of psychological experiments and delineates the conscious/unconscious distinction in terms of the two types of learning_ _and their respective products. The distinctions are captured in a two-level action-based model C_larion_. Some funda-_ _mental theoretical issues are also clari?ed with the help of the model. Comparisons with (...) existing models of conscious-_. (shrink) | |
This paper explores the interaction between implicit and explicit processes during skill learning, in terms of top-down learning (that is, learning that goes from explicit to implicit knowledge) versus bottom-up learning (that is, learning that goes from implicit to explicit knowledge). Instead of studying each type of knowledge (implicit or explicit) in isolation, we stress the interaction between the two types, especially in terms of one type giving rise to the other, and its effects on learning. The work presents an (...) integrated model of skill learning that takes into account both implicit and explicit processes and both top-down and bottom-up learning. We examine and simulate human data in the Tower of Hanoi task. The paper shows how the quantitative data in this task may be captured using either top-down or bottom-up approaches, although top-down learning is a more apt explanation of the human data currently available. These results illustrate the two different directions of learning (top-down versus bottom-up), and thereby provide a new perspective on skill learning. Ó 2003 Elsevier B.V. All rights reserved. (shrink) | |
Research in computational cognitive modeling investigates the nature of cognition through developing process-based understanding by specifying computational models of mechanisms (including representations) and processes. In this enterprise, a cognitive architecture is a domaingeneric computational cognitive model that may be used for a broad, multiple-level, multipledomain analysis of behavior. It embodies generic descriptions of cognition in computer algorithms and programs. Developing cognitive architectures is a difficult but important task. In this article, discussions of issues and challenges in developing cognitive architectures will (...) be undertaken, and an example cognitive architecture (CLARION) will be described. (shrink) | |
According to David Chalmers, the hard problem of consciousness consists of explaining how and why qualitative experience arises from physical states. Moreover, Chalmers argues that materialist and reductive explanations of mentality are incapable of addressing the hard problem. In this chapter, I suggest that Chalmers’ hard problem can be usefully distinguished into a ‘how question’ and ‘why question,’ and I argue that evolutionary biology has the resources to address the question of why qualitative experience arises from brain states. From this (...) perspective, I discuss the different kinds of evolutionary explanations (e.g., adaptationist, exaptationist, spandrel) that can explain the origins of the qualitative aspects of various conscious states. This argument is intended to clarify which parts of Chalmers’ hard problem are amenable to scientific analysis. (shrink) | |
What is creativity? One new idea may be creative, whereas another is merely new: What's the difference? And how is creativity possible? These questions about human creativity can be answered, at least in outline, using computational concepts. There are two broad types of creativity, improbabilist and impossibilist. Improbabilist creativity involves novel combinations of familiar ideas. A deeper type involves METCS: the mapping, exploration, and transformation of conceptual spaces. It is impossibilist, in that ideas may be generated which – with respect (...) to the particular conceptual space concerned – could not have been generated before. The more clearly conceptual spaces can be defined, the better we can identify creative ideas. Defining conceptual spaces is done by musicologists, literary critics, and historians of art and science. Humanist studies, rich in intuitive subtleties, can be complemented by the comparative rigour of a computational approach. Computational modelling can help to define a space, and to show how it may be mapped, explored, and transformed. Impossibilist creativity can be thought of in “classical” Al terms, whereas connectionism illuminates improbabilist creativity. Most Al models of creativity can only explore spaces, not transform them, because they have no self-reflexive maps enabling them to change their own rules. A few, however, can do so. A scientific understanding of creativity does not destroy our wonder at it, nor does it make creative ideas predictable. Demystification does not imply dehumanization. (shrink) | |
What is the potential for improvements in the functioning of consciousness? The paper addresses this issue using global workspace theory. According to this model, the prime function of consciousness is to develop novel adaptive responses. Consciousness does this by putting together new combinations of knowledge, skills and other disparate resources that are recruited from throughout the brain. The paper's search for potential improvements in consciousness is aided by studies of a developmental transition that enhances functioning in whichever domain it occurs. (...) This transition involves a shift from the use of procedural (implicit) knowledge to declarative (explicit) knowledge. However, the potential of the transition to enhance functioning has not yet been realised to any extent in relation to consciousness itself. The paper assesses the potential for consciousness to use declarative knowledge to improve its own functioning and to thereby enhance human adaptability. A number of sources (including the practices of religious and contemplative traditions) are drawn on to investigate how this potential might be realised. (shrink) | |
This paper describes how meta-cognitive processes (i.e., the self monitoring and regulating of cognitive processes) may be captured within a cognitive architecture Clarion. Some currently popular cognitive architectures lack sufficiently complex built-in meta-cognitive mechanisms. However, a sufficiently complex meta-cognitive mechanism is important, in that it is an essential part of cognition and without it, human cognition may not function properly. We contend that such a meta-cognitive mechanism should be an integral part of a cognitive architecture. Thus such a mechanism has (...) been developed within the Clarion cognitive architecture. The paper demonstrates how human data of two meta-cognitive experiments are simulated using Clarion. The simulations show that the meta-cognitive processes represented by the experimental data (and beyond) can be adequately captured within the Clarion framework. (shrink) | |
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