What is the relation between intelligence and computation? Although the difficulty of defining `intelligence' is widely recognized, many are unaware that it is hard to give a satisfactory definition of `computational' if computation is supposed to provide a non-circular explanation for intelligent abilities. The only well-defined notion of `computation' is what can be generated by a Turing machine or a formally equivalent mechanism. This is not adequate for the key role in explaining the nature of mental processes, because it is (...) too general, as many computations involve nothing mental, nor even processes: they are simply abstract structures. We need to combine the notion of `computation' with that of `machine'. This may still be too restrictive, if some non-computational mechanisms prove to be useful for intelligence. We need a theory-based taxonomy of {\em architectures} and {\em mechanisms} and corresponding process types. Computational machines my turn out to be a sub-class of the machines available for implementing intelligent agents. The more general analysis starts with the notion of a system with independently variable, causally interacting sub-states that have different causal roles, including both `belief-like' and `desire-like' sub-states, and many others. There are many significantly different such architectures. For certain architectures (including simple computers), some sub-states have a semantic interpretation for the system. The relevant concept of semantics is defined partly in terms of a kind of Tarski-like structural correspondence (not to be confused with isomorphism). This always leaves some semantic indeterminacy, which can be reduced by causal loops involving the environment. But the causal links are complex, can share causal pathways, and always leave mental states to some extent semantically indeterminate. (shrink)

In this section, we will start with an influential attempt to define `intelligence', and then we will move to a consideration of how human intelligence is to be investigated on the machine model. The last part of the section will discuss the relation between the mental and the biological.

This new volume in the acclaimed Oxford Readings in Philosophy sereis offers a selection of the most important philosophical work being done in the new and fast-growing interdisciplinary area of artificial life. Artificial life research seeks to synthesize the characteristics of life by artificial means, particularly employing computer technology. The essays here explore such fascinating themes as the nature of life, the relation between life and mind, and the limits of technology.

Artificial life can take two forms: synthetic and virtual. In principle, the materials and properties of synthetic living systems could differ radically from those of natural living systems yet still resemble them enough to be really alive if they are grounded in the relevant causal interactions with the real world. Virtual (purely computational) "living" systems, in contrast, are just ungrounded symbol systems that are systematically interpretable as if they were alive; in reality they are no more alive than a virtual (...) furnace is hot. Virtual systems are better viewed as "symbolic oracles" that can be used (interpreted) to predict and explain real systems, but not to instantiate them. The vitalistic overinterpretation of virtual life is related to the animistic overinterpretation of virtual minds and is probably based on an implicit (and possibly erroneous) intuition that living things have actual or potential mental lives. (shrink)

Metabolism is a criterion of life. Three senses are distinguished. The weakest allows strong A-Life: virtual creatures having physical existence in computer electronics, but not bodies, are classes as 'alive'. The second excludes strong A-Life but allows that some non-biochemical A-Life robots could be classed as alive. The third, which stresses the body's self-production by energy budgeting and self-equilibrating energy exchanges of some (necessary) complexity, excludes both strong A-Life and living non-biochemical robots.

In this paper we examine the following problems: How many concepts of function are there in biology, social science, and technology? Are they logically related and if so, how? Which of these function concepts effect a functional explanation as opposed to a mere functional account? What are the consequences of a pluralist view of functions for functionalism? We submit that there are five concepts of function in biology, which are logically related in a particular way, and six function concepts in (...) social science and technology. Only two of them may help effect a genuine functional explanation. Finally, our synthetic approach allows us to distinguish four different varieties of functionalism in biology, psychology, social science, and technology: formalist, black boxist, adaptationist, and teleological. And only one of them is explanatory in the strong sense defended here. (shrink)

This book is about some topical philosophical and methodological prob lems that arise in the study of behavior and mind, as well as in the treatment of behavioral and mental disorders. It deals with such questions as 'What is behavior a manifestation of?', 'What is mind, and how is it related to matter?', 'Which are the positive legacies, if any, of the major psychological schools?', 'How can behavior and mind best be studied?', and 'Which are the most effective ways of (...) modifying behavioral and mental processes?' These questions and their kin cannot be avoided in the long run because they fuel the daily search for better hypotheses, experimental designs, techniques, and treatments. They also occur in the critical examination of data and theories, as well as methods for the treatment of behavioral and mental disorders. All students of human or animal, normal or abnormal behavior and mind, whether their main concern is basic or applied, theoretical or em pirical, admit more or less tacitly to a large number of general philosophi cal and methodological principles. (shrink)

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)

The paper examines the nature of the behavioral evidence underlying attributions of intelligence in the case of human beings, and how this might be extended to other kinds of cognitive system, in the spirit of the original Turing Test. I consider Harnad's Total Turing Test, which involves successful performance of both linguistic and robotic behavior, and which is often thought to incorporate the very same range of empirical data that is available in the human case. However, I argue that the (...) TTT is still too weak, because it only tests the capabilities of particular tokens within a preexisting context of intelligent behavior. What is needed is a test of the cognitive type, as manifested through a number of exemplary tokens, in order to confirm that the cognitive type is able to produce the context of intelligent behavior presupposed by tests such as the TT and TTT. (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)

I argue that supervenience is an inadequate device for representing relations between different levels of phenomena. I then provide six criteria that emergent phenomena seem to satisfy. Using examples drawn from macroscopic physics, I suggest that such emergent features may well be quite common in the physical realm.

What is Functionalism? Functionalism is one of the major proposals that have been offered as solutions to the mind/body problem. Solutions to the mind/body problem usually try to answer questions such as: What is the ultimate nature of the mental? At the most general level, what makes a mental state mental? Or more specifically, What do thoughts have in common in virtue of which they are thoughts? That is, what makes a thought a thought? What makes a pain a pain? (...) Cartesian Dualism said the ultimate nature of the mental was to be found in a special mental substance. Behaviorism identified mental states with behavioral dispositions; physicalism in its most influential version identifies mental states with brain states. Functionalism says that mental states are constituted by their causal relations to one another and to sensory inputs and behavioral outputs. Functionalism is one of the major theoretical developments of Twentieth Century analytic philosophy, and provides the conceptual underpinnings of much work in cognitive science. (shrink)

The functionalist view of the nature of the mind is now widely accepted. Like behaviorism and physicalism, functionalism seeks to answer the question "What are mental states?" I shall be concerned with identity thesis formulations of functionalism. They say, for example, that pain is a functional state, just as identity thesis formulations of physicalism say that pain is a physical state.

In this paper, I provide further elaboration of my theory of conscious experience, in response to the criticisms made by David Cole, and I directly address a number of the issues he raises. In particular, I examine Cole's claim that functionalism rather than neurophysiology is the theoretical key to consciousness. I argue that weak type-physicalism provides an analysis which is more fine grained, makes weaker assumptions, and allows more scope for empirical methods.

The title of The Rediscovery of the Mind suggests the question "When was the mind lost?" Since most people may not be aware that it ever was lost, we must also then ask "Who lost it?" It was lost, of course, only by philosophers, by certain philosophers. This passed unnoticed by society at large. The "rediscovery" is also likely to pass unnoticed. But has the mind been rediscovered by the same philosophers who "lost" it? Probably not. John Searle is an (...) analytic philosopher, with some of the same notions as the positivists and behaviorists who rejected consciousness and "lost" the mind in the first place, but he also does not sound like the kind of reductionist who would have joined that crowd. His views, indeed, are sensible enough, and some of his insights so important, that it is a shame to find his thought profoundly limited by some of the same mistakes and prejudices that ruined philosophy, and not just philosophy of mind, under the influence of those positivists and behaviorists. There is enough of genuine value in his treatment, that it can easily be taken up and, with relatively slight modification, added to what is of permanent value in the history of philosophy. (shrink)