Because of the “all-or-none” character of nervous activity, neural events and the relations among them can be treated by means of propositional logic. It is found that the behavior of every net can be described in these terms, with the addition of more complicated logical means for nets containing circles; and that for any logical expression satisfying certain conditions, one can find a net behaving in the fashion it describes. It is shown that many particular choices among possible neurophysiological assumptions (...) are equivalent, in the sense that for every net behaving under one assumption, there exists another net which behaves under the other and gives the same results, although perhaps not in the same time. Various applications of the calculus are discussed. (shrink)

This is a book about how we see: the environment around us (its surfaces, their layout, and their colors and textures); where we are in the environment; whether or not we are moving and, if we are, where we are going; what things are good for; how to do things (to thread a needle or drive an automobile); or why things look as they do.The basic assumption is that vision depends on the eye which is connected to the brain. The (...) author suggests that natural vision depends on the eyes in the head on a body supported by the ground, the brain being only the central organ of a complete visual system. When no constraints are put on the visual system, people look around, walk up to something interesting and move around it so as to see it from all sides, and go from one vista to another. That is natural vision—and what this book is about. (shrink)

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

Much of the progress in the fields constituting cognitive science has been based upon the use of explicit information processing models, almost exclusively patterned after conventional serial computers. An extension of these ideas to massively parallel, connectionist models appears to offer a number of advantages. After a preliminary discussion, this paper introduces a general connectionist model and considers how it might be used in cognitive science. Among the issues addressed are: stability and noise‐sensitivity, distributed decision‐making, time and sequence problems, and (...) the representation of complex concepts. (shrink)

Craik published only one complete work of any length, this essay on The Nature of Explanation.

. . . Unlike Dewey, he has provided detailed incisive argumentation, and has shown just where the dogmas and dualisms break down." -- Richard Rorty, The Yale Review.

This book represents the views of one of the greatest mathematicians of the twentieth century on the analogies between computing machines and the living human brain.

This systematic investigation of computation and mental phenomena by a noted psychologist and computer scientist argues that cognition is a form of computation, that the semantic contents of mental states are encoded in the same general way as computer representations are encoded. It is a rich and sustained investigation of the assumptions underlying the directions cognitive science research is taking. 1 The Explanatory Vocabulary of Cognition 2 The Explanatory Role of Representations 3 The Relevance of Computation 4 The Psychological Reality (...) of Programs: Strong Equivalence 5 Constraining Functional Architecture 6 The Bridge from Physical to Symbolic: Transduction 7 Functional Architecture and Analogue Processes 8 Mental Imagery and Functional Architecture 9 Epilogue: What is Cognitive Science the Science of? (shrink)

What psychological and philosophical significance should we attach to recent efforts at computer simulations of human cognitive capacities? In answering this question, I find it useful to distinguish what I will call "strong" AI from "weak" or "cautious" AI. According to weak AI, the principal value of the computer in the study of the mind is that it gives us a very powerful tool. For example, it enables us to formulate and test hypotheses in a more rigorous and precise fashion. (...) But according to strong AI, the computer is not merely a tool in the study of the mind; rather, the appropriately programmed computer really is a mind, in the sense that computers given the right programs can be literally said to. (shrink)

What is needed today is a biologically grounded explanation of behavior, one that moves beyond the so?called mind?body problem. Yet no solution will be found by philosophers who refuse to learn about how brains and bodies work, or by neuroscientists pursuing experimental research based on outmoded or blatantly anti?biological theories. Churchland's book proposes a solution: to come by a unified theory of the mind?brain philosophers have to work together with neuroscientists. Yet Churchland's vision of a unified theory is based on (...) an assumption that, while widely held, may not adequately reflect brain functioning in the production of behavior, namely, the assumption that brain processes represent. The present paper proposes an alternative view, suggesting that patterns of neural activity do not ?represent? anything, that brains do not ?read? or ?transform? representations, and that brains do not require representations to produce goal?directed behavior. Representations are replaced by self?organizing neural processes that achieve a certain end?state of interaction between the organism and its environment in a flexible and adaptive manner. Some of the implications of this view for neuroscientific research and the philosophy of mind are outlined. (shrink)

Approaches to the Study of Man In this chapter we shall distinguish two broad approaches to the study of human behaviour, the natural scientific, ...