A set of hypotheses is formulated for a connectionist approach to cognitive modeling. These hypotheses are shown to be incompatible with the hypotheses underlying traditional cognitive models. The connectionist models considered are massively parallel numerical computational systems that are a kind of continuous dynamical system. The numerical variables in the system correspond semantically to fine-grained features below the level of the concepts consciously used to describe the task domain. The level of analysis is intermediate between those of symbolic cognitive models (...) and neural models. The explanations of behavior provided are like those traditional in the physical sciences, unlike the explanations provided by symbolic models. (shrink)

In this paper, I explore the implications of recent empirical research on concept representation for the philosophical enterprise of conceptual analysis. I argue that conceptual analysis, as it is commonly practiced, is committed to certain assumptions about the nature of our intuitive categorization judgments. I then try to show how these assumptions clash with contemporary accounts of concept representation in cognitive psychology. After entertaining an objection to my argument, I close by considering ways in which conceptual analysis might be altered (...) to accord better with the empirical work. (shrink)

Most biologists and some cognitive scientists have independently reached the conclusion that there is no such thing as learning in the traditional “instructive‘ sense. This is, admittedly, a somewhat extreme thesis, but I defend it herein the light of data and theories jointly extracted from biology, especially from evolutionary theory and immunology, and from modern generative grammar. I also point out that the general demise of learning is uncontroversial in the biological sciences, while a similar consensus has not yet been (...) reached in psychology and in linguistics at large. Since many arguments presently offered in defense of learning and in defense of “general intelligence‘ are often based on a distorted picture of human biological evolution, I devote some sections of this paper to a critique of “adaptationism,‘ providing also a sketch of a better evolutionary theory. Moreover, since certain standard arguments presented today as “knock-down‘ in psychology, in linguistics and in artificial intelligence are a perfect replica of those once voiced by biologists in favor of instruction and against selection, I capitalize on these errors of the past to draw some lessons for the present and for the future. (shrink)

This book develops a new naturalist theory of reason and scientific knowledge from a synthesis of philosophy and the new sciences of complex adaptive systems.

In his bookMinimal Rationality (1986), Christopher Cherniak draws deep and widespread conclusions from our finitude, and not only for philosophy but also for a wide range of science as well. Cherniak's basic idea is that traditional philosophical theories of rationality represent idealisations that are inaccessible to finite rational agents. It is the purpose of this paper to apply a theory of idealisation in science to Cherniak's arguments. The heart of the theory is a distinction between idealisations that represent reversible, solely (...) quantitative simplifications and those that represent irreversible, degenerate idealisations which collapse out essential theoretical structure. I argue that Cherniak's position is best understood as assigning the latter status to traditional rationality theories and that, so understood, his arguments may be illuminated, expanded, and certain common criticisms of them rebutted. The result, however, is a departure from traditional, formalist theories of rationality of a more radical kind than Cherniak contemplates, with widespread ramifications for philosophical theory, especially philosophy of science itself. (shrink)

This book presents a clear and critical view of the orthodox logical empiricist tradition, pointing the way to significant developments for the understanding of science both as research and as culture.

Feyerabrend argues that intellectual progress relies on the creativity of the scientist, against the authority of science.

A Neurocomputationial Perspective illustrates the fertility of the concepts and data drawn from the study of the brain and of artificial networks that model the...

Professor Brown describes and criticises the major classical model of rationality and offers a new model of this central concept in the history of philosophy and of science.

" --Maurice A. Finocchiaro,Isis "The best and most original aspect of the book is its overall conception.

Something remarkable is happening in the cognitive sciences. After a quarter of a century of cognitive models that were inspired by the metaphor of the digital computer, the newest cognitive models are inspired by the properties of the brain itself. Variously referred to as connectionist, parallel distributed processing, or neutral network models, they explore the idea that complex intellectual operations can be carried out by large networks of simple, neuron-like units. The units themselves are identical, very low-level and 'stupid'. Intelligent (...) performance is derived from the pattern of connection strengths between units, and the fundamental cognitive activity is pattern recognition and completion. Connectionism and the Mind provides an introduction to this newly emerging approach to understanding the mind. The first few chapters focus on network architecture, offering accessible treatment of the equations that describe learning and the propagation of activation. Furthermore, the reader is walked step-by-step through the activities of networks engaged in pattern recognition, learning, and cognitive tasks such as memory retrieval and prototype formation. The remainder of the book addresses the implications of connectionism for theories of the mind, both philosophical and psychological. Foe example: What Role is played by pattern recognition and completion as basic as cognitive functions? Connectionist models have particular strength in learning and pattern recognition; should they be limited to those functions, or can they provide an overall account of cognitive functioning? In particular, can connectionist models provide an adequate account of the ability to employ linguistic and other symbol systems, or must an adequate system incorporate symbol processing as a basic cognitive capacity? Finally, Connectionism and the Mind examines the relation of connectionist models to philosophical accounts of propositional attitudes, and to a variety of other inquiries in cognitive psychology, linguistics, developmental psychology, artificial intelligence and neuroscience. (shrink)

Papers presented cover: new approaches to evolutionary epistemology, new applications, critical evaluations, and the nature of the mind. Paper edition (unseen), $25.50. Annotation copyrighted by Book News, Inc., Portland, OR.

Essays discuss relativism, knowledge, creativity, progress, Aristotle, Galileo, cultural pluralism, and reason.