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Metaphors for mindIn the next few sections I review some of the theoretical frameworks that have emerged in the last half-century, starting with psychology and progressively introducing ideas from Artificial Intelligence and, most recently, formal theories of knowledge and mental states. I shall start with the work of two famous scientists, Donald Broadbent and Alan Newell, who provide a useful springboard for the discussion. This choice is somewhat arbitrary, in that I wish to remember two of my personal mentors, but they are also important and representative figures in complementary fields of cognitive science. At a time when ideas from neuroscience and from computational science are becoming increasingly successful, but also moving apart, it may be useful to remember them and the intellectual continuity they represent.
Statics: minds as information processing architectures
"A nervous systems acts to some extent as a single communication channel, so that it is meaningful to regard it as having a limited capacity. ... incoming information may be held in a temporary store at a stage previous to the limited capacity channel:.... The maximum time of storage possible in this way is of the order of seconds."
D E. Broadbent Perception and Communication (1958) 297-298.
Donald Broadbent (1926-1993) was director of the Medical Research Council's Applied Psychology Unit in Cambridge, England. He made many contributions concerning the organisation and integration of human cognitive functions, like memory, attention and decision-making, drawing on experimental investigations and detailed observations of the complex demands that real-world environments place on human beings. His applied focus gave him a keen awareness that cognitive functions are strongly affected by environmental factors like high noise and other stressors and their interaction with physiological parameters. His engineering training also allowed him to see how the information theory that developed during and after the global conflict of 1939-45 could shed light on these processes. The centrepiece of Perception and Communication (1958), the book that established his reputation, visualised functions like memory, attention and decision-making in an image of the mind as an information processing system made up of a number of interacting physical components (figure 2).
“Box and arrow” diagrams of the sort that Broadbent used have continued to be a popular way of providing an image of mental processes in psychology because, under fairly simple interpretation rules, the organisation of the components often seems to yield unambiguous, and experimentally testable, predictions about human behaviour. Box and arrow conventions can also be used at different scales, from the detailed processes involved in recognising words to the high-level Richard Cooper of Birkbeck College London has observed that it would be valuable to have standard conventions for modelling cognitive "modules", their properties and their interrelationships. His suggestion has been put to practical use in the COGENT cognitive modelling system illustrated in figure 4 (Cooper and Fox, 1998; Cooper, 2002). COGENT is a flexible tool for describing the static organisation of cognitive systems, and has been used extensively for constructing models of natural systems and designing artificial ones (see Cooper 2000 and also Glasspool’s chapter in this volume). It provides a standard way of visualising cognitive components, a range of predefined “cognitive modules” and a practical visual design environment. Cell biologists use generally accepted conventions for visualising static aspects of cellular processes for explanation and teaching, such as 3D molecular models and metabolic pathways drawn as flow graphs. Cognitive scientists have similar needs but often use diagrams as a basis for predicting behaviour as well. COGENT offers clear conventions for describing static cognitive organisation graphically and, as we see in the next section, a precise and unambiguous language for specifying the properties of the system and hence predicting its behaviour.
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