John Searle's Speech Acts (1969) and Expression and Meaning (1979) developed a highly original and influential approach to the study of language. But behind both works lay the assumption that the philosophy of language is in the end a branch of the philosophy of the mind: speech acts are forms of human action and represent just one example of the mind's capacity to relate the human organism to the world. The present book is concerned with these biologically fundamental capacities, and, (...) though third in the sequence, in effect it provides the philosophical foundations for the other two. Intentionality is taken to be the crucial mental phenomenon, and its analysis involves wide-ranging discussions of perception, action, causation, meaning, and reference. In all these areas John Searle has original and stimulating views. He ends with a resolution of the 'mind-body' problem. (shrink)

John Searle's Speech Acts (1969) and Expression and Meaning (1979) developed a highly original and influential approach to the study of language. But behind both works lay the assumption that the philosophy of language is in the end a branch of the philosophy of the mind: speech acts are forms of human action and represent just one example of the mind's capacity to relate the human organism to the world. The present book is concerned with these biologically fundamental capacities, and, (...) though third in the sequence, in effect it provides the philosophical foundations for the other two. Intentionality is taken to be the crucial mental phenomenon, and its analysis involves wide-ranging discussions of perception, action, causation, meaning, and reference. In all these areas John Searle has original and stimulating views. He ends with a resolution of the 'mind-body' problem. (shrink)

A classic source for understanding the connections between information theory and physics, this text was written by one of the giants of 20th-century physics and is appropriate for upper-level undergraduates and graduate students. Topics include the principles of coding, coding problems and solutions, the analysis of signals, a summary of thermodynamics, thermal agitation and Brownian motion, and thermal noise in an electric circuit. A discussion of the negentropy principle of information introduces the author's renowned examination of Maxwell's demon. Concluding chapters (...) explore the associations between information theory, the uncertainty principle, and physical limits of observation, in addition to problems related to computing, organizing information, and inevitable errors. 1962 ed. 81 figures. 14 tables. (shrink)

Ethologists and others studying animal behavior in a spirit are in need of a descriptive language and method that are neither anachronistically bound by behaviorist scruples nor prematurely committed to particular Just such an interim descriptive method can be found in intentional system theory. The use of intentional system theory is illustrated with the case of the apparently communicative behavior of vervet monkeys. A way of using the theory to generate data - including usable, testable data - is sketched. The (...) underlying assumptions of this approach can be seen to ally it directly with theorizing in evolutionary biology, which has recently come under attack from Stephen Gould and Richard Lewontin, who castigate it as the Their arguments, which are strongly analogous to B. F, Skinner's arguments against point to certain pitfalls that attend the careless exercise of such thinking (and rival varieties of thinking as well), but do not constitute a fundamental objection to either adaptationist theorizing or its cousin, intentional system theory. (shrink)

This paperback edition contains a preface placing the book in the context of recent work in the area.

This collection of 17 essays by the author offers a comprehensive theory of mind, encompassing traditional issues of consciousness and free will.

A study in the philosophy of science, proposing a strong form of the doctrine of scientific realism' and developing its implications for issues in the philosophy of mind.

The present essay is addressed simultaneously to two distinct audiences.

First published in 1976, this book presents a view of language as a matter of systematic communicative behaviour.

We must, therefore, make a study of mechanism; but some introduction is advisable, for cybernetics treats the subject from a new, and therefore unusual, ...

The concept of an ecological niche (econiche) has been used in a variety of ways, some of which are incompatible with a relational or functional interpretation of the term. This essay seeks to standardize usage by limiting the concept to functional relations between organisms and their surroundings, and to revise the concept to include epistemic relations. For most organisms, epistemics are a vital aspect of their functional relationships to their surroundings and, hence, a major determinant of their econiche. Rejecting the (...) traditional dualism of organism and environment, an econiche is defined as the reciprocal (dual) of a functionally specified class of organisms (FSTU). From this perspective, an econiche necessarily implies a certain type of organism, and a class of functionally similar organisms implies a special econiche.The econiche concept is also discussed in relation to other ecological terms that reflect the distributional patterns of organisms, such as habitat, and the concept of an empty niche is criticized. (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)

I propose to consider the question, "Can machines think?" This should begin with definitions of the meaning of the terms "machine" and "think." The definitions might be framed so as to reflect so far as possible the normal use of the words, but this attitude is dangerous, If the meaning of the words "machine" and "think" are to be found by examining how they are commonly used it is difficult to escape the conclusion that the meaning and the answer to (...) the question, "Can machines think?" is to be sought in a statistical survey such as a Gallup poll. But this is absurd. Instead of attempting such a definition I shall replace the question by another, which is closely related to it and is expressed in relatively unambiguous words. The new form of the problem can be described in terms of a game which we call the 'imitation game." It is played with three people, a man (A), a woman (B), and an interrogator (C) who may be of either sex. The interrogator stays in a room apart front the other two. The object of the game for the interrogator is to determine which of the other two is the man and which is the woman. He knows them by labels X and Y, and at the end of the game he says either "X is A and Y is B" or "X is B and Y is A." The interrogator is allowed to put questions to A and B. We now ask the question, "What will happen when a machine takes the part of A in this game?" Will the interrogator decide wrongly as often when the game is played like this as he does when the game is played between a man and a woman? These questions replace our original, "Can machines think?". (shrink)

A pioneering work in the philosophy of mind, Content and Consciousness brings together the approaches of philosophers and scientists to the mind--a connection that must occur if genuine analysis of the mind is to be made. This unified approach permits the most forbiddingly mysterious mental phenomenon--consciousness--to be broken down into several distinct phenomena, and these are each given a foundation in the physical activity of the brain. This paperback edition contains a preface placing the book in the context of recent (...) work in the area. (shrink)

The paper explores the distinction between two doctrines, both of which inform theory construction in much of modern cognitive psychology: the representational theory of mind and the computational theory of mind. According to the former, propositional attitudes are to be construed as relations that organisms bear to mental representations. According to the latter, mental processes have access only to formal (nonsemantic) properties of the mental representations over which they are defined.The following claims are defended: (1) That the traditional dispute between (...) “rational” and “naturalistic” psychology is plausibly viewed as an argument about the status of the computational theory of mind. Rational psychologists accept a formality condition on the specification of mental processes; naturalists do not. (2) That to accept the formality condition is to endorse a version of methodological solipsism. (3) That the acceptance of some such condition is warranted, at least for that part of psychology which concerns itself with theories of the mental causation of behavior. This is because: (4) such theories require nontransparent taxonomies of mental states; and (5) nontransparent taxonomies individuate mental states without reference to their semantic properties. Equivalently, (6) nontransparent taxonomies respect the way that the organism represents the object of its propositional attitudes toitself, and it is this representation which functions in the causation of behavior.The final section of the paper considers the prospect for a naturalistic psychology: one which defines its generalizations over relations between mental representations and their environmental causes, thus seeking to account for the semantic properties of propositional attitudes. Two related arguments are proposed, both leading to the conclusion that no such research strategy is likely to prove fruitful. (shrink)

2015 Reprint of 1956 Printing. Full facsimile of the original edition. Not reproduced with Optical Recognition Software. Cybernetics is here defined as "the science of control and communication, in the animal and the machine"-in a word, as the art of steersmanship; and this book will interest all who are interested in cybernetics, communication theory and methods for regulation and control. W. Ross Ashby (1903-1972) was an English psychiatrist and a pioneer in cybernetics, the study of complex systems. His two books, (...) "Design for a Brain" and "An Introduction to Cybernetics," were landmark works. They introduced exact and logical thinking into the nascent discipline and were highly influential. Contents include: What is new -- Change -- The Determinate Machine -- The Machine with Input -- Stability -- The Black Box -- Quantity of Variety -- Transmission of Variety -- Incessant Transmission -- Regulation in Biological Systems -- Requisite Variety -- The Error-controlled Regulator -- Regulating the Very Large System -- Amplifying Regulation. (shrink)

The mathematical theory of communication.

Semantic Engines: An Introduction to Mind Design, John C. Haugeland; Computer Science as Empirical Inquiry: Symbols and Search, Alan Newell and Herbert A. Simon; Complexity and the Study of Artificial and Human Intelligence, Zenon Pylyshyn; A Framework for Representing Knowledge, Marvin Minsky; Artificial Intelligence---A Personal View, David Marr; Artificial Intelligence Meets Natural Stupidity, Drew McDermott; From Micro-Worlds to Knowledge Representation: AI at an Impasse, Hubert L. Dreyfus; Reductionism and the Nature of Psychology, Hilary Putnam; Intentional Systems, Daniel C. Dennett; The (...) Nature and Plausibility of Cognitivism, John C. Haugeland; Minds, Brains, and Programs, John R. Searle; MethodologicalSolipsism Considered as a Research Strategy in Cognitive Psychology, Jerry A. Fodor; The Material Mind, Donald Davidson. (shrink)

Cognitive Science is likely to make little progress in the study of human behavior until we have a clear account of what a human action is. The aim of this paper is to present a sketch of a theory of action. I will locate the relation of intention to action within a general theory of Intentionality. I will introduce a distinction between prior intentions and intentions in actions; the concept of the experience of acting; and the thesis that both prior (...) intentions and intentions in action are causally selfreferential. Each of these is independently motivated, but together they enable me to suggest solutions to several outstanding problems within action theory (deviant causal chains, the accordian effect, basic actions, etc.), to show how the logical structure of intentional action is strikingly like the logical structure of perceptions, and to construct an account of simple actions. A successfully performed intentional action characteristically consists of an intention in action together with the bodily movement or state of the agent which is its condition of satisfaction and which is caused by it. The account is extended to complex actions. (shrink)

Cognitive Science is likely to make little progress in the study of human behavior until we have a clear account of what a human action is. The aim of this paper is to present a sketch of a theory of action. I will locate the relation of intention to action within a general theory of Intentionality. I will introduce a distinction between prior intentions and intentions in actions; the concept of the experience of acting; and the thesis that both prior (...) intentions and intentions in action are causally selfreferential. Each of these is independently motivated, but together they enable me to suggest solutions to several outstanding problems within action theory (deviant causal chains, the accordian effect, basic actions, etc.), to show how the logical structure of intentional action is strikingly like the logical structure of perceptions, and to construct an account of simple actions. A successfully performed intentional action characteristically consists of an intention in action together with the bodily movement or state of the agent which is its condition of satisfaction and which is caused by it. The account is extended to complex actions. (shrink)

This book, published in 1976, presents an entirely original approach to the subject of the mind-body problem, examining it in terms of the conceptual links between the physical sciences and the sciences of human behaviour. It is based on the cybernetic concepts of information and feedback and on the related concepts of thermodynamic and communication-theoretic entropy. The foundation of the approach is the theme of continuity between evolution, learning and human consciousness. The author defines life as a process of energy (...) exchange between organism and environment, and evolution as a feedback process maintaining equilibrium between environment and reproductive group. He demonstrates that closely related feedback processes on the levels of the behaving organism and of the organism’s nervous system constitute the phenomena of learning and consciousness respectively. He analyses language as an expedient for extending human information-processing and control capacities beyond those provided by one’s own nervous system, and shows reason to be a mode of processing information in the form of concepts removed from immediate stimulus control. The last chapter touches on colour vision, pleasure and pain, intentionality, self-awareness and other subjective phenomena. Of special interest to the communication theorist and philosopher, this study is also of interest to psychologists and anyone interested in the connection between the physical and life sciences. (shrink)

The computational view of mind rests on certain intuitions regarding the fundamental similarity between computation and cognition. We examine some of these intuitions and suggest that they derive from the fact that computers and human organisms are both physical systems whose behavior is correctly described as being governed by rules acting on symbolic representations. Some of the implications of this view are discussed. It is suggested that a fundamental hypothesis of this approach is that there is a natural domain of (...) human functioning that can be addressed exclusively in terms of a formal symbolic or algorithmic vocabulary or level of analysis. Much of the paper elaborates various conditions that need to be met if a literal view of mental activity as computation is to serve as the basis for explanatory theories. The coherence of such a view depends on there being a principled distinction between functions whose explanation requires that we posit internal representations and those that we can appropriately describe as merely instantiating causal physical or biological laws. In this paper the distinction is empirically grounded in a methodological criterion called the " cognitive impenetrability condition." Functions are said to be cognitively impenetrable if they cannot be influenced by such purely cognitive factors as goals, beliefs, inferences, tacit knowledge, and so on. Such a criterion makes it possible to empirically separate the fixed capacities of mind from the particular representations and algorithms used on specific occasions. In order for computational theories to avoid being ad hoc, they must deal effectively with the "degrees of freedom" problem by constraining the extent to which they can be arbitrarily adjusted post hoc to fit some particular set of observations. This in turn requires that the fixed architectural function and the algorithms be independently validated. It is argued that the architectural assumptions implicit in many contemporary models run afoul of the cognitive impenetrability condition, since the required fixed functions are demonstrably sensitive to tacit knowledge and goals. The paper concludes with some tactical suggestions for the development of computational cognitive theories. (shrink)

It is argued that the traditional distinction between artificial intelligence and cognitive simulation amounts to little more than a difference in style of research - a different ordering in goal priorities and different methodological allegiances. Both enterprises are constrained by empirical considerations and both are directed at understanding classes of tasks that are defined by essentially psychological criteria. Because of the different ordering of priorities, however, they occasionally take somewhat different stands on such issues as the power/generality trade-off and on (...) the relevance of the sort of data collected in experimental psychology laboratories. (shrink)