Article

Information processing, computation, and cognition.

Journal of Biological Physics (Impact Factor: 1.15). 01/2011; 37(1):1-38. DOI: 10.1007/s10867-010-9195-3
Source: OAI

ABSTRACT Computation and information processing are among the most fundamental notions in cognitive science. They are also among the most imprecisely discussed. Many cognitive scientists take it for granted that cognition involves computation, information processing, or both - although others disagree vehemently. Yet different cognitive scientists use 'computation' and 'information processing' to mean different things, sometimes without realizing that they do. In addition, computation and information processing are surrounded by several myths; first and foremost, that they are the same thing. In this paper, we address this unsatisfactory state of affairs by presenting a general and theory-neutral account of computation and information processing. We also apply our framework by analyzing the relations between computation and information processing on one hand and classicism, connectionism, and computational neuroscience on the other. We defend the relevance to cognitive science of both computation, at least in a generic sense, and information processing, in three important senses of the term. Our account advances several foundational debates in cognitive science by untangling some of their conceptual knots in a theory-neutral way. By leveling the playing field, we pave the way for the future resolution of the debates' empirical aspects.

1 Follower
 · 
116 Views
  • [Show abstract] [Hide abstract]
    ABSTRACT: This paper seeks to understand machine cognition. The nature of machine cognition has been shrouded in incomprehensibility. We have often encountered familiar arguments in cognitive science that human cognition is still faintly understood. This paper will argue that machine cognition is far less understood than even human cognition despite the fact that a lot about computer architecture and computational operations is known. Even if there have been putative claims about the transparency of the notion of machine computations, these claims do not hold out in unraveling machine cognition, let alone machine consciousness (if there is any such thing). The nature and form of machine cognition remains further confused also because of attempts to explain human cognition in terms of computation and to model/simulate (aspects of) human cognitive processing in machines. Given that these problems in characterizing machine cognition persist, a view of machine cognition that aims to avoid these problems is outlined. The argument that is advanced is that something becomes a computation in machines only when a human interprets it, which is a kind of semiotic causation. From this it follows that a computing machine is not engaged in a computation unless a human interprets what it is doing; instead, it is engaged in machine cognition, which is defined as a member or subset of the set of all possible mappings of inputs to outputs. The human interpretation, which is a semiotic process, gives meaning to what a machine does, and then what it does becomes a computation.
    Biosemiotics 04/2013; 7(1):97-110. DOI:10.1007/s12304-013-9179-3 · 0.49 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: This paper will deal with how and in what ways ( linguistic) computation as part of linguistic competence may relate to aspects of culture in the context of the cognition which becomes viable by being grounded in the possible conjunction of mental computations and cultural praxis. The possibilities of cultural capacities are enormous across societies and/or cultures, but linguistic computations as have been postulated are restricted by the nature of constraints specific to natural language. The purpose of this paper is to see the consequences of how these two can make cognition viable. (C) 2013 The Authors. Published by Elsevier Ltd.
    Procedia - Social and Behavioral Sciences 11/2013; 97:464-473. DOI:10.1016/j.sbspro.2013.10.260
  • 09/2014; 27(3):441-459. DOI:10.1007/s13347-014-0164-9

Full-text (3 Sources)

Download
36 Downloads
Available from
May 26, 2014