Two experiments investigated the mental representation of spatial and nonspatial two-dimensional problems. The experiments were designed to contrast opposite predictions of the model theory of reasoning and the formal rules of inference theories. Half of the problems required more inferential steps but only one model, whereas the other half required fewer inferential steps but two models. According to the inference rules, theory problems that require more inferential steps should be harder, whereas the model-based theory predicts that problems that require two (...) models should be harder. In Experiments 1a and 1b we measured the problem solving time and the percentage of errors. In Experiments 2a and 2b the problems were presented segmented in two different displays. We measured the comprehension time for each display, the question answering times, and the percentage of errors. The results of all experiments supported the model theory predictions in both spatial and nonspatial domains. (shrink)

Contemporary epistemology has assumed that knowledge is represented in sentences or propositions. However, a variety of extensions and alternatives to this view have been proposed in other areas of investigation. We review some of these proposals, focusing on (1) Ryle's notion of knowing how and Hanson's and Kuhn's accounts of theory-laden perception in science; (2) extensions of simple propositional representations in cognitive models and artificial intelligence; (3) the debate concerning imagistic versus propositional representations in cognitive psychology; (4) recent treatments of (...) concepts and categorization which reject the notion of necessary and sufficient conditions; and (5) parallel distributed processing (connectionist) models of cognition. This last development is especially promising in providing a flexible, powerful means of representing information nonpropositionally, and carrying out at least simple forms of inference without rules. Central to several of the proposals is the notion that much of human cognition might consist in pattern recognition rather than manipulation of rules and propositions. (shrink)

Summary. The viability of the proposal that human cognition involves the utilization of nonsentential models is seriously undercut by the fact that no one has yet given a satisfactory account of how neurophysiological circuitry might realize representations of the right sort. Such an account is offered up here, the general idea behind which is that high-level models can be realized by lower—level computations and, in turn, by neural machinations. It is shown that this account can be usefully applied to deal (...) with problems in fields ranging from artificial intelligence to the philosophy of science. (shrink)