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Unified Theories of Cognition

Harvard University Press (1990)

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  1. Intentionality, Mind and Folk Psychology.Winand H. Dittrich & Stephen E. G. Lea - 1993 - Behavioral and Brain Sciences 16 (1):39-41.
    The comment addresses central issues of a "theory theory" approach as exemplified in Gopnik' and Goldman's BBS-articles. Gopnik, on the one hand, tries to demonstrate that empirical evidence from developmental psychology supports the view of a "theory theory" in which common sense beliefs are constructed to explain ourselves and others. Focusing the informational processing routes possibly involved we would like to argue that his main thesis (e.g. idea of intentionality as a cognitive construct) lacks support at least for two reasons: (...)
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  • A Preference Semantics for Imperatives.William B. Starr - 2020 - Semantics and Pragmatics 20.
    Imperative sentences like Dance! do not seem to represent the world. Recent modal analyses challenge this idea, but its intuitive and historical appeal remain strong. This paper presents three new challenges for a non-representational analysis, showing that the obstacles facing it are even steeper than previously appreciated. I will argue that the only way for the non-representationalist to meet these three challenges is to adopt a dynamic semantics. Such a dynamic semantics is proposed here: imperatives introduce preferences between alternatives. This (...)
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  • Desiderata for Cognitive Architectures.Ron Sun - 2004 - Philosophical Psychology 17 (3):341-373.
    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 (...)
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  • Limitless Capacity: A Dynamic Object-Oriented Approach to Short-Term Memory.Bill Macken, John Taylor & Dylan Jones - 2015 - Frontiers in Psychology 6.
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  • Bounded Rationality and Heuristics in Humans and in Artificial Cognitive Systems.Antonio Lieto - 2019 - Isonomía. Revista de Teoría y Filosofía Del Derecho 1 (4):1-21.
    In this paper I will present an analysis of the impact that the notion of “bounded rationality”, introduced by Herbert Simon in his book “Administrative Behavior”, produced in the field of Artificial Intelligence (AI). In particular, by focusing on the field of Automated Decision Making (ADM), I will show how the introduction of the cognitive dimension into the study of choice of a rational (natural) agent, indirectly determined - in the AI field - the development of a line of research (...)
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  • Social Institution, Cognition, and Survival: A Cognitive–Social Simulation.Ron Sun & Isaac Naveh - 2007 - Mind and Society 6 (2):115-142.
    Although computational models of cognitive agents that incorporate a wide range of cognitive functionalities have been developed in cognitive science, most of the work in social simulation still assumes rudimentary cognition on the part of the agents. In contrast, in this work, the interaction of cognition and social structures/processes is explored, through simulating survival strategies of tribal societies. The results of the simulation demonstrate interactions between cognitive and social factors. For example, we show that cognitive capabilities and tendencies may be (...)
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  • Casimir: An Architecture for Mental Spatial Knowledge Processing.Holger Schultheis & Thomas Barkowsky - 2011 - Topics in Cognitive Science 3 (4):778-795.
    Mental spatial knowledge processing often uses spatio-analogical or quasipictorial representation structures such as spatial mental models or mental images. The cognitive architecture Casimir is designed to provide a framework for computationally modeling human spatial knowledge processing relying on these kinds of representation formats. In this article, we present an overview of Casimir and its components. We briefly describe the long-term memory component and the interaction with external diagrammatic representations. Particular emphasis is placed on Casimir’s working memory and control mechanisms. Regarding (...)
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  • The End of Development.Sergio Balari & Guillermo Lorenzo - 2015 - Biological Theory 10 (1):60-72.
    Recently, there has been a growing interest, both within theoretical biology and the philosophy of biology, in the possibility and desirability of a theory of development. Among the many issues raised within this debate, the questions of the spatial and temporal boundaries of development have received particular attention. In this article, noting that so far the discussion has mostly centered on the processes of morphogenesis and organogenesis, we argue that an important missing element in the equation, namely the development of (...)
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  • Why Representation(s) Will Not Go Away: Crisis of Concept or Crisis of Theory?René Jorna & Barend van Heusden - 2003 - Semiotica 2003 (143).
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  • Decision Making, Semiosis, and the Knowledge Space: The Case for Studas.R. J. Jorna - 2001 - Semiotica 2001 (133).
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  • On Central Cognition.Peter Carruthers - 2014 - Philosophical Studies 170 (1):143-162.
    This article examines what is known about the cognitive science of working memory, and brings the findings to bear in evaluating philosophical accounts of central cognitive processes of thinking and reasoning. It is argued that central cognition is sensory based, depending on the activation and deployment of sensory images of various sorts. Contrary to a broad spectrum of philosophical opinion, the central mind does not contain any workspace within which goals, decisions, intentions, or non-sensory judgments can be active.Introduction: philosophers’ commitmentsMost (...)
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  • Modelos Din'micos Aplicados À Aprendizagem de Valores Em Inteligência Artificial.Nicholas Kluge Corrêa & Nythamar De Oliveira - 2020 - Veritas – Revista de Filosofia da Pucrs 65 (2):e37439.
    Especialistas em desenvolvimento de Inteligência Artificial prevêem que o avanço no desenvolvimento de sistemas e agentes inteligentes irá remodelar áreas vitais em nossa sociedade. Contudo, se tal avanço não for realizado de maneira prudente e crítico-reflexiva, pode resultar em desfechos negativos para a humanidade. Por este motivo, diversos pesquisadores na área têm desenvolvido uma concepção de IA robusta, benéfica e segura para a preservação da humanidade e do meio-ambiente. Atualmente, diversos dos problemas em aberto no campo de pesquisa em IA (...)
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  • A Cognitive Social Simulation of Tribal Survival Strategies: The Importance of Cognitive and Motivational Factors.Ron Sun & Pierson Fleischer - 2012 - Journal of Cognition and Culture 12 (3-4):287-321.
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  • Memory for Goals: An Activation‐Based Model.Erik M. Altmann & J. Gregory Trafton - 2002 - Cognitive Science 26 (1):39-83.
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  • Incubation, Insight, and Creative Problem Solving: A Unified Theory and a Connectionist Model.Ron Sun - 2010 - Psychological Review 117 (3):994-1024.
    This article proposes a unified framework for understanding creative problem solving, namely, the explicit–implicit interaction theory. This new theory of creative problem solving constitutes an attempt at providing a more unified explanation of relevant phenomena (in part by reinterpreting/integrating various fragmentary existing theories of incubation and insight). The explicit–implicit interaction theory relies mainly on 5 basic principles, namely, (a) the coexistence of and the difference between explicit and implicit knowledge, (b) the simultaneous involvement of implicit and explicit processes in most (...)
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  • Model Theory of Deduction: A Unified Computational Approach.Bruno G. Bara, Monica Bucciarelli & Vincenzo Lombardo - 2001 - Cognitive Science 25 (6):839-901.
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  • Cognitive Architectures and Multi-Agent Social Simulation.Ron Sun - unknown
    As we know, a cognitive architecture is a domain-generic computational cognitive model that may be used for a broad analysis of cognition and behavior. Cognitive architectures embody theories of cognition in computer algorithms and programs. Social simulation with multi-agent systems can benefit from incorporating cognitive architectures, as they provide a realistic basis for modeling individual agents (as argued in Sun 2001). In this survey, an example cognitive architecture will be given, and its application to social simulation will be sketched.
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  • On Distinguishing Epistemic From Pragmatic Action.David Kirsh & Paul Maglio - 1994 - Cognitive Science 18 (4):513-49.
    We present data and argument to show that in Tetris - a real-time interactive video game - certain cognitive and perceptual problems are more quickly, easily, and reliably solved by performing actions in the world rather than by performing computational actions in the head alone. We have found that some translations and rotations are best understood as using the world to improve cognition. These actions are not used to implement a plan, or to implement a reaction; they are used to (...)
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  • Unconscious Representations 2: Towards an Integrated Cognitive Architecture.Luis M. Augusto - 2014 - Axiomathes 24 (1):19-43.
    The representational nature of human cognition and thought in general has been a source of controversies. This is particularly so in the context of studies of unconscious cognition, in which representations tend to be ontologically and structurally segregated with regard to their conscious status. However, it appears evolutionarily and developmentally unwarranted to posit such segregations, as,otherwise, artifact structures and ontologies must be concocted to explain them from the viewpoint of the human cognitive architecture. Here, from a by-and-large Classical cognitivist viewpoint, (...)
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  • A Cybernetic Computational Model for Learning and Skill Acquisition.B. Scott & A. Bansal - 2013 - Constructivist Foundations 9 (1):125-136.
    Context: Although there are rich descriptive accounts of skill acquisition in the literature, there are no satisfactory explanatory models of the cognitive processes involved. Problem: The aim of the paper is to explain some key phenomena frequently observed in the acquisition of motor skills: the loss of conscious access to knowledge of the structure of a skill and the awareness that an error has been made prior to the receipt of knowledge of results. Method: In the 1970s, the first author (...)
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  • Integration and Reuse in Cognitive Skill Acquisition.Dario D. Salvucci - 2013 - Cognitive Science 37 (5):829-860.
    Previous accounts of cognitive skill acquisition have demonstrated how procedural knowledge can be obtained and transformed over time into skilled task performance. This article focuses on a complementary aspect of skill acquisition, namely the integration and reuse of previously known component skills. The article posits that, in addition to mechanisms that proceduralize knowledge into more efficient forms, skill acquisition requires tight integration of newly acquired knowledge and previously learned knowledge. Skill acquisition also benefits from reuse of existing knowledge across disparate (...)
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  • Modeling Parallelization and Flexibility Improvements in Skill Acquisition: From Dual Tasks to Complex Dynamic Skills.Niels Taatgen - 2005 - Cognitive Science 29 (3):421-455.
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  • On Levels of Cognitive Modeling.Ron Sun, Andrew Coward & Michael J. Zenzen - 2005 - Philosophical Psychology 18 (5):613-637.
    The article first addresses the importance of cognitive modeling, in terms of its value to cognitive science (as well as other social and behavioral sciences). In particular, it emphasizes the use of cognitive architectures in this undertaking. Based on this approach, the article addresses, in detail, the idea of a multi-level approach that ranges from social to neural levels. In physical sciences, a rigorous set of theories is a hierarchy of descriptions/explanations, in which causal relationships among entities at a high (...)
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  • Cognitive Social Simulation Incorporating Cognitive Architectures.Ron Sun - unknown
    Agent-based social simulation (with multi-agent systems), which is an important aspect of social computing, can benefit from incorporating cognitive architectures, as they provide a realistic basis for modeling individual agents and therefore their social interactions. A cognitive architecture is a domain-generic computational cognitive model that may be used for a broad multiple-domain analysis of individual behavior. In this article, an example of a cognitive architecture is given, and its applications to social simulation described. Some challenging issues in this regard are (...)
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  • Motivational Representations Within a Computational Cognitive Architecture.Ron Sun - unknown
    This paper discusses essential motivational representations necessary for a comprehensive computational cognitive architecture. It hypothesizes the need for implicit drive representations, as well as explicit goal representations. Drive representations consist of primary drives — both low-level primary drives (concerned mostly with basic physiological needs) and high-level primary drives (concerned more with social needs), as well as derived (secondary) drives. On the basis of drives, explicit goals may be generated on the fly during an agent’s interaction with various situations. These motivational (...)
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  • Theoretical Status of Computational Cognitive Modeling.Ron Sun - unknown
    This article explores the view that computational models of cognition may constitute valid theories of cognition, often in the full sense of the term ‘‘theory”. In this discussion, this article examines various (existent or possible) positions on this issue and argues in favor of the view above. It also connects this issue with a number of other relevant issues, such as the general relationship between theory and data, the validation of models, and the practical benefits of computational modeling. All the (...)
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  • The Importance of Cognitive Architectures: An Analysis Based on CLARION.Ron Sun - unknown
    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 (...)
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  • Methodological Considerations in Studying Awareness During Learning. Part 2: Second Language Acquisition.Daisuke Nakamura - 2013 - Polish Psychological Bulletin 44 (3):337-353.
    This paper considers methodological issues of awareness during adult second language acquisition. Specifically, the paper deals with the issue of instructional orientations, the issue of biases in knowledge measurement, and the issue of reactivity in the online think-aloud protocol. Detailed reviews of prominent SLA research that has investigated the possibility of implicit SLA reveal that the instruction on implicit learning does not guarantee that learners engage in the implicit learning mode, that the majority of SLA research has employed only tests (...)
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  • Introductory Article: The Mind-Society Problem.Riccardo Viale - 2000 - Mind and Society 1 (1):3-24.
    The mind-society problem deals with the relations between mental and social phenomena. The problem is crucial in the main methodologies of social sciences. The thesis of hermeneutics is that we can only understand but not explain the relationship between beliefs and social action because mental and social events are not natural events. The thesis of social holism is that social phenomena are emergent and irreducible to mental phenomena. The thesis of rational choice theory is that social phenomena are reducible to (...)
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  • Top-Down Versus Bottom-Up Learning in Cognitive Skill Acquisition.Ron Sun - unknown
    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 (...)
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  • The Interaction of the Explicit and the Implicit in Skill Learning: A Dual-Process Approach.Ron Sun - 2005 - Psychological Review 112 (1):159-192.
    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 (...)
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  • The Mind as Neural Software? Understanding Functionalism, Computationalism, and Computational Functionalism.Gualtiero Piccinini - 2010 - Philosophy and Phenomenological Research 81 (2):269-311.
    Defending or attacking either functionalism or computationalism requires clarity on what they amount to and what evidence counts for or against them. My goalhere is not to evaluatc their plausibility. My goal is to formulate them and their relationship clearly enough that we can determine which type of evidence is relevant to them. I aim to dispel some sources of confusion that surround functionalism and computationalism. recruit recent philosophical work on mechanisms and computation to shed light on them, and clarify (...)
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  • There is No Need for (Even Fully Fleshed Out) Mental Models to Map Onto Formal Logic.Paul Pollard - 1993 - Behavioral and Brain Sciences 16 (2):363-364.
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  • A Perspective for Viewing the History of Psychophysics.David J. Murray - 1993 - Behavioral and Brain Sciences 16 (1):115-137.
    Fechner's conception of psychophysics included both “outer psychophysics” the relation between stimulus intensity and the response reflecting sensation strength, and “inner psychophysics” the relation between neurelectric responses and sensation strength. In his own time outer psychophysics focussed on the form of the psychophysical law, with Fechner espousing a logarithmic law, Delboeuf a variant of the logarithmic law incorporating a resting level of neural activity, and Plateau a power law. One of the issues on which the dispute was focussed concerned the (...)
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  • Précis of Deduction.Philip N. Johnson-Laird & Ruth M. J. Byrne - 1993 - Behavioral and Brain Sciences 16 (2):323-333.
    How do people make deductions? The orthodox view in psychology is that they use formal rules of inference like those of a “natural deduction” system.Deductionargues that their logical competence depends, not on formal rules, but on mental models. They construct models of the situation described by the premises, using their linguistic knowledge and their general knowledge. They try to formulate a conclusion based on these models that maintains semantic information, that expresses it parsimoniously, and that makes explicit something not directly (...)
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  • Précis of Beyond Modularity: A Developmental Perspective on Cognitive Science.Annette Karmiloff-Smith - 1994 - Behavioral and Brain Sciences 17 (4):693-707.
    Beyond modularityattempts a synthesis of Fodor's anticonstructivist nativism and Piaget's antinativist constructivism. Contra Fodor, I argue that: the study of cognitive development is essential to cognitive science, the module/central processing dichotomy is too rigid, and the mind does not begin with prespecified modules; rather, development involves a gradual process of “modularization.” Contra Piaget, I argue that: development rarely involves stagelike domain-general change and domainspecific predispositions give development a small but significant kickstart by focusing the infant's attention on proprietary inputs. Development (...)
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  • From Numerical Concepts to Concepts of Number.Lance J. Rips, Amber Bloomfield & Jennifer Asmuth - 2008 - Behavioral and Brain Sciences 31 (6):623-642.
    Many experiments with infants suggest that they possess quantitative abilities, and many experimentalists believe that these abilities set the stage for later mathematics: natural numbers and arithmetic. However, the connection between these early and later skills is far from obvious. We evaluate two possible routes to mathematics and argue that neither is sufficient: (1) We first sketch what we think is the most likely model for infant abilities in this domain, and we examine proposals for extrapolating the natural number concept (...)
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  • The Central Role of Heuristic Search in Cognitive Computation Systems.Wai-Tat Fu - 2016 - Minds and Machines 26 (1-2):103-123.
    This paper focuses on the relation of heuristic search and level of intelligence in cognitive computation systems. The paper begins with a review of the fundamental properties of a cognitive computation system, which is defined generally as a control system that generates goal-directed actions in response to environmental inputs and constraints. An important property of cognitive computations is the need to process local cues in symbol structures to access and integrate distal knowledge to generate a response. To deal with uncertainties (...)
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  • Addiction as Vulnerabilities in the Decision Process.A. David Redish, Steve Jensen & Adam Johnson - 2008 - Behavioral and Brain Sciences 31 (4):461-487.
    In our target article, we proposed that addiction could be envisioned as misperformance of a decision-making machinery described by two systems (deliberative and habit systems). Several commentators have argued that Pavlovian learning also produces actions. We agree and note that Pavlovian action-selection will provide several additional vulnerabilities. Several commentators have suggested that addiction arises from sociological parameters. We note in our response how sociological effects can change decision-making variables to provide additional vulnerabilities. Commentators generally have agreed that our theory provides (...)
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  • A Unified Framework for Addiction: Vulnerabilities in the Decision Process.A. David Redish, Steve Jensen & Adam Johnson - 2008 - Behavioral and Brain Sciences 31 (4):415-437.
    The understanding of decision-making systems has come together in recent years to form a unified theory of decision-making in the mammalian brain as arising from multiple, interacting systems (a planning system, a habit system, and a situation-recognition system). This unified decision-making system has multiple potential access points through which it can be driven to make maladaptive choices, particularly choices that entail seeking of certain drugs or behaviors. We identify 10 key vulnerabilities in the system: (1) moving away from homeostasis, (2) (...)
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  • On the Ability to Inhibit Thought and Action: General and Special Theories of an Act of Control.Gordon D. Logan, Trisha Van Zandt, Frederick Verbruggen & Eric-Jan Wagenmakers - 2014 - Psychological Review 121 (1):66-95.
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  • Elme És Evolúció.Bence Nanay - 2000 - Kávé..
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  • How Designers Work - Making Sense of Authentic Cognitive Activities.Henrik Gedenryd - 1998 - Dissertation, Lund University
    In recent years, the growing scientific interest in design has led to great advances in our knowledge of authentic design processes. However, as these findings go counter to the existing theories in both design research and cognitive science, they pose a serious challenge for both disciplines: there is a wide gap between what the existing theories predict and what designers actually do. At the same time, there is a growing movement of research on authentic cognitive activities, which has among other (...)
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  • Classical Computational Models.Richard Samuels - 2018 - In Mark Sprevak & Matteo Colombo (ed.), The Routledge Handbook of the Computational Mind. Oxford, UK: pp. 103-119.
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  • Addressing Information Systems Failures Through Design Research.Terence Love - unknown
    The ubiquitousness of failures in new information systems designs and implementations indicates that the design methodologies that the field has developed are inadequate or faulty. This paper points to the body of knowledge developed from design research as a potential source of expertise for developing design methods that are more successful. The paper describes a meta-theoretical method for classifying theories in the Information Systems field, and identifying areas that need farther development.
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  • Towards a Multi-Level Exploration of Human and Computational Re-Representation in Unified Cognitive Frameworks.Ana-Maria Olteţeanu, Mikkel Schöttner & Arpit Bahety - 2019 - Frontiers in Psychology 10.
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  • Cognition and the Structure of Bias.Gabbrielle Johnson - 2019 - Dissertation, University of California, Los Angeles
    I argue that there exists a natural kind social bias that subsumes seemingly heterogenous cases of implicit bias and other forms of social cognition. I explore the implications of this explicated notion of bias for the organization of the mind, theories of consciousness, and the system-dependence of biases.
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  • Philosophy of the Cognitive Sciences.William Bechtel & Mitchell Herschbach - 2010 - In Fritz Allhoff (ed.), Philosophies of the Sciences. Wiley-Blackwell. pp. 239--261.
    Cognitive science is an interdisciplinary research endeavor focusing on human cognitive phenomena such as memory, language use, and reasoning. It emerged in the second half of the 20th century and is charting new directions at the beginning of the 21st century. This chapter begins by identifying the disciplines that contribute to cognitive science and reviewing the history of the interdisciplinary engagements that characterize it. The second section examines the role that mechanistic explanation plays in cognitive science, while the third focuses (...)
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  • Case-by-Case Problem Solving.Pei Wang - 2009 - In B. Goertzel, P. Hitzler & M. Hutter (eds.), Proceedings of the Second Conference on Artificial General Intelligence. Atlantis Press. pp. 180--185.
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  • Directions in Connectionist Research: Tractable Computations Without Syntactically Structured Representations.Jonathan A. Waskan & William P. Bechtel - 1997 - Metaphilosophy 28 (1‐2):31-62.
    Figure 1: A pr ototyp ical exa mple of a three-layer feed forward network, used by Plunkett and M archm an (1 991 ) to simulate learning the past-tense of En glish verbs. The inpu t units encode representations of the three phonemes of the present tense of the artificial words used in this simulation. Th e netwo rk is trained to produce a representation of the phonemes employed in the past tense form and the suffix (/d/, /ed/, or /t/) (...)
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