Switch to: References

Add citations

You must login to add citations.
  1. From Implausible Artificial Neurons to Idealized Cognitive Models: Rebooting Philosophy of Artificial Intelligence.Catherine Stinson - 2020 - Philosophy of Science 87 (4):590-611.
    There is a vast literature within philosophy of mind that focuses on artificial intelligence, but hardly mentions methodological questions. There is also a growing body of work in philosophy of science about modeling methodology that hardly mentions examples from cognitive science. Here these discussions are connected. Insights developed in the philosophy of science literature about the importance of idealization provide a way of understanding the neural implausibility of connectionist networks. Insights from neurocognitive science illuminate how relevant similarities between models and (...)
    Download  
     
    Export citation  
     
    Bookmark   8 citations  
  • Additive Factors Do Not Imply Discrete Processing Stages: A Worked Example Using Models of the Stroop Task.Tom Stafford & Kevin N. Gurney - 2011 - Frontiers in Psychology 2.
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  • Précis of semantic cognition: A parallel distributed processing approach.Timothy T. Rogers & James L. McClelland - 2008 - Behavioral and Brain Sciences 31 (6):689-714.
    In this prcis we focus on phenomena central to the reaction against similarity-based theories that arose in the 1980s and that subsequently motivated the approach to semantic knowledge. Specifically, we consider (1) how concepts differentiate in early development, (2) why some groupings of items seem to form or coherent categories while others do not, (3) why different properties seem central or important to different concepts, (4) why children and adults sometimes attest to beliefs that seem to contradict their direct experience, (...)
    Download  
     
    Export citation  
     
    Bookmark   21 citations  
  • Shortlist B: A Bayesian model of continuous speech recognition.Dennis Norris & James M. McQueen - 2008 - Psychological Review 115 (2):357-395.
    Download  
     
    Export citation  
     
    Bookmark   66 citations  
  • The Past, Present, and Future of Cognitive Architectures.Niels Taatgen & John R. Anderson - 2010 - Topics in Cognitive Science 2 (4):693-704.
    Cognitive architectures are theories of cognition that try to capture the essential representations and mechanisms that underlie cognition. Research in cognitive architectures has gradually moved from a focus on the functional capabilities of architectures to the ability to model the details of human behavior, and, more recently, brain activity. Although there are many different architectures, they share many identical or similar mechanisms, permitting possible future convergence. In judging the quality of a particular cognitive model, it is pertinent to not just (...)
    Download  
     
    Export citation  
     
    Bookmark   7 citations  
  • Computational Mechanisms and Models of Computation.Marcin Miłkowski - 2014 - Philosophia Scientiae 18:215-228.
    In most accounts of realization of computational processes by physical mechanisms, it is presupposed that there is one-to-one correspondence between the causally active states of the physical process and the states of the computation. Yet such proposals either stipulate that only one model of computation is implemented, or they do not reflect upon the variety of models that could be implemented physically. In this paper, I claim that mechanistic accounts of computation should allow for a broad variation of models of (...)
    Download  
     
    Export citation  
     
    Bookmark   3 citations  
  • The Place of Modeling in Cognitive Science.James L. McClelland - 2009 - Topics in Cognitive Science 1 (1):11-38.
    I consider the role of cognitive modeling in cognitive science. Modeling, and the computers that enable it, are central to the field, but the role of modeling is often misunderstood. Models are not intended to capture fully the processes they attempt to elucidate. Rather, they are explorations of ideas about the nature of cognitive processes. In these explorations, simplification is essential—through simplification, the implications of the central ideas become more transparent. This is not to say that simplification has no downsides; (...)
    Download  
     
    Export citation  
     
    Bookmark   23 citations  
  • Marr’s Three Levels: A Re-evaluation. [REVIEW]Ron McClamrock - 1990 - Minds and Machines 1 (May):185-196.
    the _algorithmic_, and the _implementational_; Zenon Pylyshyn (1984) calls them the _semantic_, the _syntactic_, and the _physical_; and textbooks in cognitive psychology sometimes call them the levels of _content_, _form_, and _medium_ (e.g. Glass, Holyoak, and Santa 1979).
    Download  
     
    Export citation  
     
    Bookmark   33 citations  
  • Marr's Levels Revisited: Understanding How Brains Break.Valerie G. Hardcastle & Kiah Hardcastle - 2015 - Topics in Cognitive Science 7 (2):259-273.
    While the research programs in early cognitive science and artificial intelligence aimed to articulate what cognition was in ideal terms, much research in contemporary computational neuroscience looks at how and why brains fail to function as they should ideally. This focus on impairment affects how we understand David Marr's hypothesized three levels of understanding. In this essay, we suggest some refinements to Marr's distinctions using a population activity model of cortico-striatal circuitry exploring impulsivity and behavioral inhibition as a case study. (...)
    Download  
     
    Export citation  
     
    Bookmark   8 citations  
  • 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 (...)
    Download  
     
    Export citation  
     
    Bookmark   1118 citations  
  • Using extra output learning to insert a symbolic theory into a connectionist network.M. R. W. Dawson, D. A. Medler, D. B. McCaughan, L. Willson & M. Carbonaro - 2000 - Minds and Machines 10 (2):171-201.
    This paper examines whether a classical model could be translated into a PDP network using a standard connectionist training technique called extra output learning. In Study 1, standard machine learning techniques were used to create a decision tree that could be used to classify 8124 different mushrooms as being edible or poisonous on the basis of 21 different Features (Schlimmer, 1987). In Study 2, extra output learning was used to insert this decision tree into a PDP network being trained on (...)
    Download  
     
    Export citation  
     
    Bookmark   2 citations  
  • The how and why of what went where in apparent motion: Modeling solutions to the motion correspondence problem.Michael R. Dawson - 1991 - Psychological Review 98 (4):569-603.
    Download  
     
    Export citation  
     
    Bookmark   30 citations  
  • Neural constraints in cognitive science.Keith Butler - 1994 - Minds and Machines 4 (2):129-62.
    The paper is an examination of the ways and extent to which neuroscience places constraints on cognitive science. In Part I, I clarify the issue, as well as the notion of levels in cognitive inquiry. I then present and address, in Part II, two arguments designed to show that facts from neuroscience are at a level too low to constrain cognitive theory in any important sense. I argue, to the contrary, that there are several respects in which facts from neurophysiology (...)
    Download  
     
    Export citation  
     
    Bookmark   5 citations  
  • Levels of description and explanation in cognitive science.William Bechtel - 1994 - Minds and Machines 4 (1):1-25.
    The notion of levels has been widely used in discussions of cognitive science, especially in discussions of the relation of connectionism to symbolic modeling of cognition. I argue that many of the notions of levels employed are problematic for this purpose, and develop an alternative notion grounded in the framework of mechanistic explanation. By considering the source of the analogies underlying both symbolic modeling and connectionist modeling, I argue that neither is likely to provide an adequate analysis of processes at (...)
    Download  
     
    Export citation  
     
    Bookmark   71 citations  
  • Spanning seven orders of magnitude: a challenge for cognitive modeling.John R. Anderson - 2002 - Cognitive Science 26 (1):85-112.
    Much of cognitive psychology focuses on effects measured in tens of milliseconds while significant educational outcomes take tens of hours to achieve. The task of bridging this gap is analyzed in terms of Newell's (1990) bands of cognition—the Biological, Cognitive, Rational, and Social Bands. The 10 millisecond effects reside in his Biological Band while the significant learning outcomes reside in his Social Band. The paper assesses three theses: The Decomposition Thesis claims that learning occurring at the Social Band can be (...)
    Download  
     
    Export citation  
     
    Bookmark   17 citations  
  • Outline of a new approach to the nature of mind.Dr Petros A. M. Gelepithis - 2009
    I propose a new approach to the constitutive problem of psychology ‘what is mind?’ The first section introduces modifications of the received scope, methodology, and evaluation criteria of unified theories of cognition in accordance with the requirements of evolutionary compatibility and of a mature science. The second section outlines the proposed theory. Its first part provides empirically verifiable conditions delineating the class of meaningful neural formations and modifies accordingly the traditional conceptions of meaning, concept and thinking. This analysis is part (...)
    Download  
     
    Export citation  
     
    Bookmark