The relationship of mind and matter is approached in a new way in this article. This approach is based on the causal interpretation of the quantum theory, in which an electron, for example, is regarded as an inseparable union of a particle and afield. This field has, however, some new properties that can be seen to be the main sources of the differences between the quantum theory and the classical (Newtonian) theory. These new properties suggest that the field may be (...) regarded as containing objective and active information, and that the activity of this information is similar in certain key ways to the activity of information in our ordinary subjective experience. The analogy between mind and matter is thus fairly close. This analogy leads to the proposal of the general outlines of a new theory of mind, matter, and their relationship, in which the basic notion is participation rather than interaction. Although the theory can be developed mathematically in more detail, the main emphasis here is to show qualitatively how it provides a way of thinking that does not divide mind from matter, and thus leads to a more coherent understanding of such questions than is possible in the common dualistic and reductionistic approaches. These ideas may be relevant to connectionist theories and might perhaps suggest new directions for their development. (shrink)

Embodied Cognition is an approach to cognition that departs from traditional cognitive science in its reluctance to conceive of cognition as computational and in its emphasis on the significance of an organism's body in how and what the organism thinks. Three lines of embodied cognition research are described and some thoughts on the future of embodied cognition offered.

The objective of this paper is to reconsider the relationship between marxism and existential-phenomenological sociology in light of margolis' (1978) recent articulation and systematic defense of what he terms nonreductive materialism--a material monist ontology which acknowledges an irreducible dualism of attributes. it is argued that reductive materialism is philosophically indefensible and that the most important reasons for thinking that marxism entails reductive materialism are mistaken.

A fundamental problem in artificial intelligence is that nobody really knows what intelligence is. The problem is especially acute when we need to consider artificial systems which are significantly different to humans. In this paper we approach this problem in the following way: we take a number of well known informal definitions of human intelligence that have been given by experts, and extract their essential features. These are then mathematically formalised to produce a general measure of intelligence for arbitrary machines. (...) We believe that this equation formally captures the concept of machine intelligence in the broadest reasonable sense. We then show how this formal definition is related to the theory of universal optimal learning agents. Finally, we survey the many other tests and definitions of intelligence that have been proposed for machines. (shrink)

Phenomenologists such as Merleau?Ponty have argued that the ordinary teleological relation between an embodied agent and the world is neither ?subjective? nor ?cognitive?, i.e. that it is not normally mediated by a chain of explicit cognition occurring within a distinct mental subject. Yet, while this seems true from a first?person, phenomenological perspective, I argue that teleological forms of explanation require the ascription of Intentional states. Intentional states, however, are usually regarded as subjective, cognitive states. In order to reconcile the phenomenology (...) with the logic of teleology, I introduce the notion of ?body?intentionality?. I maintain that we can use a modified version of Jonathan Bennett's concept of a teleological law to specify third?person empirical criteria for a pre?cognitive, pre?subjective kind of Intentionality. I also argue that this notion of body?intentionality provides us with at least a partial solution to the mind?body problem that avoids the inadequacies of the computational theory of mind. (shrink)

The idea that human thinking and machine computing are "radically the same" provides the central theme for this marvelously lucid and witty book on...

There are different ways to present a Presidential Address to the APA; the one I have chosen is simply to report on work that I am doing right now, on work in progress. I am going to present some of my further explorations into the computational model of the mind.\**.

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.

The dominant scientific and philosophical view of the mind – according to which, put starkly, cognition is computation – is refuted herein, via specification and defense of the following new argument: Computation is reversible; cognition isn't; ergo, cognition isn't computation. After presenting a sustained dialectic arising from this defense, we conclude with a brief preview of the view we would put in place of the cognition-is-computation doctrine.

In this paper I link two hitherto disconnected sets of results in the philosophy of emotions and explore their implications for the computational theory of mind. The argument of the paper is that, for just the same reasons that some computationalists have thought that cognition may be a natural kind, so the same can plausibly be argued of emotion. The core of the argument is that emotions are a representation-governed phenomenon and that the explanation of how they figure in behaviour (...) must as such be undertaken in those terms. I conclude with some interdisciplinary reflections in defence of the hypothesis that emotions might be more fundamental in the organization of behaviour than cognition; that, in effect, we may be emoters before we are cognizers . The aim of the paper is: (1) to introduce a number of promising results in philosophical and empirical emotion theory to a wider audience; and (2) to begin the task of organizing those results into a computational theoretical framework. (shrink)

Kripke (1982, Wittgenstein on rules and private language. Cambridge, MA: MIT Press) presents a rule-following paradox in terms of what we meant by our past use of “plus”, but the same paradox can be applied to any other term in natural language. Many responses to the paradox concentrate on fixing determinate meaning for “plus”, or for a small class of other natural language terms. This raises a problem: how can these particular responses be generalised to the whole of natural language? (...) In this paper, I propose a solution. I argue that if natural language is computable in a sense defined below, and the Church–Turing thesis is accepted, then this auxiliary problem can be solved. (shrink)

This paper critiques the view, widely held by philosophers of mind and cognitive scientists, that psychological explanation is a matter of ascribing propositional attitudes (such as beliefs and desires) towards language-like propositions in the mind, and that cognitive mental states consist in intentional attitudes towards propositions of a linguistic quasi-linguistic nature. On this view, thought is structured very much like a language. Denial that propositional attitude psychology is an adequate account of mind is therefore, on this view, is tantamount to (...) eliminative materialism, the denial that human beings are thinking beings. -/- I dispute this on the basis of recent work in cognitive psychology and artificial intelligence. Mental models theory, on which thought is better understood as nonpropositional intentional psychology, accords better with the evidence and offers an alternative view to propositional attitude psychology -- one that means that the denial that that is propositional is not eliminative. However, I argue that propositional attitude psychology is a useful idealization, as classical mechanics is of relativity theory, strictly but not radically false, and useful for prediction and indeed, as long as its idealized character is born in mind, for explanation of behavior. (shrink)

The intentional stance is the strategy of prediction and explanation that attributes beliefs, desires, and other states to systems and predicts future behavior from what it would be rational for an agent to do, given those beliefs and desires. Any system whose performance can be thus predicted and explained is an intentional system, whatever its innards. The strategy of treating parts of the world as intentional systems is the foundation of but is also exploited in artificial intelligence and cognitive science (...) more generally, as well as in evolutionary theory. An analysis of the role of the intentional stance and its presuppositions supports a naturalistic theory of mental states and events, their content or intentionality, and the relation between levels of explanation and neurophysiological or mechanistic levels of explanation. As such, the analysis of the intentional stance grounds a theory of the mind and its relation to the body. (shrink)

This chapter reviews some interesting research trends in the philosophy of information (PI). First, PI is defined; then, a series of open problems in PI on which philosophers are currently working is considered. The conclusion highlights the innovative character of this new area of research.

Recent experiments have shown that when individuals with a substance use disorder are confronted with drug-related cues, they exhibit an automatically activated tendency to approach these cues. The strength of the drug approach bias has been associated with clinically relevant measures, such as increased drug craving and relapse, and activations in brain reward areas. Retraining the approach bias by means of cognitive bias modification has been demonstrated to decrease relapse rates in patients with an alcohol use disorder and to reduce (...) alcohol cue-evoked limbic activity. Here, we review empirical and theoretical literature on the drug approach bias and explore two distinct models of how the drug approach bias may be embodied. First, we consider the “biological meaning” hypothesis, which grounds the automatic approach bias in the natural meaning of the body. Second, we consider the “sensorimotor hypothesis,” which appeals to the specific sensorimotor loops involved in the instantiation of addictive behaviors as the basis of the automatic approach bias. In order to differentiate between the adequacies of these competing explanations, we present specific, predictions that each model should make. (shrink)

This introduction to a special issue of Topoi introduces and summarises the relationship between three main varieties of 'enactivist' theorising about the mind: 'autopoietic', 'sensorimotor', and 'radical' enactivism. It includes a brief discussion of the philosophical and cognitive scientific precursors to enactivist theories, and the relationship of enactivism to other trends in embodied cognitive science and philosophy of mind.

In this review of Hutto and Myin's Radicalizing Enactivism, I question the adequacy of a non-representational theory of mind. I argue first that such a theory cannot differentiate cognition from other bodily engagements such as wrestling with an opponent. Second, I question whether the simple robots constructed by Rodney Brooks are adequate as models of multimodal organisms. Last, I argue that Hutto and Myin pay very little attention to how semantically interacting representations are needed to give an account of choice (...) and action. (shrink)

Is it true that if zombies---creatures who are behaviorally indistinguishable from us, but no more conscious than a rock-are logically possible, the computational conception of mind is false? Are zombies logically possible? Are they physically possible? This paper is a careful, sustained argument for affirmative answers to these three questions.

The philosophy of information (PI) is a new area of research with its own field of investigation and methodology. This article, based on the Herbert A. Simon Lecture of Computing and Philosophy I gave at Carnegie Mellon University in 2001, analyses the eighteen principal open problems in PI. Section 1 introduces the analysis by outlining Herbert Simon's approach to PI. Section 2 discusses some methodological considerations about what counts as a good philosophical problem. The discussion centers on Hilbert's famous analysis (...) of the central problems in mathematics. The rest of the article is devoted to the eighteen problems. These are organized into five sections: problems in the analysis of the concept of information, in semantics, in the study of intelligence, in the relation between information and nature, and in the investigation of values. (shrink)

Over the past several decades, the philosophical community has witnessed the emergence of an important new paradigm for understanding the mind.1 The paradigm is that of machine computation, and its influence has been felt not only in philosophy, but also in all of the empirical disciplines devoted to the study of cognition. Of the several strategies for applying the resources provided by computer and cognitive science to the philosophy of mind, the one that has gained the most attention from philosophers (...) has been the Computational Theory of Mind (CTM). CTM was first articulated by Hilary Putnam (1960, 1961), but finds perhaps its most consistent and enduring advocate in Jerry Fodor (1975, 1980, 1981, 1987, 1990, 1994). It is this theory, and not any broader interpretations of what it would be for the mind to be a computer, that I wish to address in this paper. What I shall argue here is that the notion of symbolic representation employed by CTM is fundamentally unsuited to providing an explanation of the intentionality of mental states (a major goal of CTM), and that this result undercuts a second major goal of CTM, sometimes refered to as the vindication of intentional psychology. This line of argument is related to the discussions of derived intentionality by Searle (1980, 1983, 1984) and Sayre (1986, 1987). But whereas those discussions seem to be concerned with the causal dependence of familiar sorts of symbolic representation upon meaning-bestowing acts, my claim is rather that there is not one but several notions of meaning to be had, and that the notions that are applicable to symbols are conceptually dependent upon the notion that is applicable to mental states in the fashion that Aristotle refered to as paronymy. That is, an analysis of the notions of meaning applicable to symbols reveals that they contain presuppositions about meaningful mental states, much as Aristotle's analysis of the sense of healthy that is applied to foods reveals that it means conducive to having a healthy body, and hence any attempt to explain mental semantics in terms of the semantics of symbols is doomed to circularity and regress. I shall argue, however, that this does not have the consequence that computationalism is bankrupt as a paradigm for cognitive science, as it is possible to reconstruct CTM in a fashion that avoids these difficulties and makes it a viable research framework for psychology, albeit at the cost of losing its claims to explain intentionality and to vindicate intentional psychology. I have argued elsewhere (Horst, 1996) that local special sciences such as psychology do not require vindication in the form of demonstrating their reducibility to more fundamental theories, and hence failure to make good on these philosophical promises need not compromise the broad range of work in empirical cognitive science motivated by the computer paradigm in ways that do not depend on these problematic treatments of symbols. (shrink)

Searle’s celebrated Chinese room thought experiment was devised as an attempted refutation of the view that appropriately programmed digital computers literally are the possessors of genuine mental states. A standard reply to Searle, known as the “robot reply” (which, I argue, reflects the dominant approach to the problem of content in contemporary philosophy of mind), consists of the claim that the problem he raises can be solved by supplementing the computational device with some “appropriate” environmental hookups. I argue that not (...) only does Searle himself casts doubt on the adequacy of this idea by applying to it a slightly revised version of his original argument, but that the weakness of this encoding-based approach to the problem of intentionality can also be exposed from a somewhat different angle. Capitalizing on the work of several authors and, in particular, on that of psychologist Mark Bickhard, I argue that the existence of symbol-world correspondence is not a property that the cognitive system itself can appreciate, from its own perspective, by interacting with the symbol and therefore, not a property that can constitute intrinsic content. The foundational crisis to which Searle alluded is, I conclude, very much alive. (shrink)

This article responds to two unresolved and crucial problems of cognitive science: (1) What is actually accomplished by functions of the nervous system that we ordinarily describe in the intentional idiom? and (2) What makes the information processing involved in these functions semantic? It is argued that, contrary to the assumptions of many cognitive theorists, the computational approach does not provide coherent answers to these problems, and that a more promising start would be to fall back on mathematical communication theory (...) and, with the help of evolutionary biology and neurophysiology, to attempt a characterization of the adaptive processes involved in visual perception. Visual representations are explained as patterns of cortical activity that are enabled to focus on objects in the changing visual environment by constantly adjusting to maintain levels of mutual information between pattern and object that are adequate for continuing perceptual control. In these terms, the answer proposed to (1) is that the intentional functions of vision are those involved in the establishment and maintenance of such representations, and to (2) that semantic features are added to the information processes of vision with the focus on objects that these representations accomplish. The article concludes with proposals for extending this account of intentionality to the higher domains of conceptualization and reason, and with speculation about how semantic information-processing might be achieved in mechanical systems. (shrink)

This entry provides a substantive overview of research and debates concerning creativity in philosophy and related fields. Topics covered include definitions of creativity, whether creativity can be learned, whether it can be explained, attempts to explain creativity in cognitive science, and whether computer programs or AI systems can be creative.

John Haugeland's Mind design and Mind design II are organized around the idea that the fundamental idea of cognitive science is that, “intelligent beings are semantic engines — in other words, automatic formal systems with interpretations under which they consistently make sense”. The goal of artificial intelligence research, or the problem of “mind design” as Haugeland calls it, is to develop computers that are in fact semantic engines. This paper canvasses the changes in artificial intelligence research reflected in the different (...) selections of essays found in each volume. While Mind design II is a worthy successor to Mind design, there are some notable developments in artificial intelligence which suggest that seemingly intelligent behavior need not be guided by semantic engines at all. (shrink)

The psychological condition of being happy is best understood as a matter of a person’s emotional condition. I elucidate the notion of an emotional condition by introducing two distinctions concerning affect, and argue that this “emotional state” view is probably superior on intuitive and substantive grounds to theories that identify happiness with pleasure or life satisfaction. Life satisfaction views, for example, appear to have deflationary consequences for happiness’ value. This would make happiness an unpromising candidate for the central element in (...) a theory of well-being, as it is in L. W. Sumner’s work. Yet on an emotional state conception, happiness may prove to be a key constituent of well-being. The emotional state view also makes happiness less vulnerable to common doubts about the importance of happiness, and indicates that mood states are more important for well-being than is generally recognized. (shrink)

The relationship of mind and matter is approached in a new way in this article. This approach is based on the causal interpretation of the quantum theory, in which an electron, for example, is regarded as an inseparable union of a particle and afield. This field has, however, some new properties that can be seen to be the main sources of the differences between the quantum theory and the classical (Newtonian) theory. These new properties suggest that the field may be (...) regarded as containing objective and active information, and that the activity of this information is similar in certain key ways to the activity of information in our ordinary subjective experience. The analogy between mind and matter is thus fairly close. This analogy leads to the proposal of the general outlines of a new theory of mind, matter, and their relationship, in which the basic notion is participation rather than interaction. Although the theory can be developed mathematically in more detail, the main emphasis here is to show qualitatively how it provides a way of thinking that does not divide mind from matter, and thus leads to a more coherent understanding of such questions than is possible in the common dualistic and reductionistic approaches. These ideas may be relevant to connectionist theories and might perhaps suggest new directions for their development. (shrink)

The view that the brain is a sort of computer has functioned as a theoretical guideline both in cognitive science and, more recently, in neuroscience. But since we can view every physical system as a computer, it has been less than clear what this view amounts to. By considering in some detail a seminal study in computational neuroscience, I first suggest that neuroscientists invoke the computational outlook to explain regularities that are formulated in terms of the information content of electrical (...) signals. I then indicate why computational theories have explanatory force with respect to these regularities:in a nutshell, they underscore correspondence relations between formal/mathematical properties of the electrical signals and formal/mathematical properties of the represented objects. I finally link my proposal to the philosophical thesis that content plays an essential role in computational taxonomy. (shrink)

Cognitive science has been dominated by the computational conception that cognition is computation across representations. To the extent to which cognition as computation across representations is supposed to be a purposive, meaningful, algorithmic, problem-solving activity, however, computers appear to be incapable of cognition. They are devices that can facilitate computations on the basis of semantic grounding relations as special kinds of signs. Even their algorithmic, problem-solving character arises from their interpretation by human users. Strictly speaking, computers as such — apart (...) from human users — are not only incapable of cognition, but even incapable of computation, properly construed. If we want to understand the nature of thought, then we have to study thinking, not computing, because they are not the same thing. (shrink)

The purpose of this article is to show why consciousness and thought are not manifested in digital computers. Analyzing the rationale for claiming that the formal manipulation of physical symbols in Turing machines would emulate human thought, the article attempts to show why this proved false. This is because the reinterpretation of designation and meaning to accommodate physical symbol manipulation eliminated their crucial functions in human discourse. Words have denotations and intensional meanings because the brain transforms the physical stimuli received (...) from the microworld into a qualitative, macroscopic representation for consciousness. Lacking this capacity as programmed machines, computers have no representations for their symbols to designate and mean. Unlike human beings in which consciousness and thought, with their inherent content, have emerged because of their organic natures, serial processing computers or parallel distributed processing systems, as programmed electrical machines, lack these causal capacities. (shrink)

In this paper I review some leading developments in the empirical theory of affect. I argue that (1) affect is a distinct perceptual representation governed system, and (2) that there are significant modular factors in affect. The paper concludes with the observation thatfeeler (affective perceptual system) may be a natural kind within cognitive science. The main purpose of the paper is to explore some hitherto unappreciated connections between the theory of affect and the computational theory of mind.

Abstract I first suggest some ways in which the externalist account of psychological content can be reconciled with the aspectual character of intentionality. I then give an argument against the externalist account which includes as premises the claims that a system capable of having intentional states must understand a language, and that a system that understands a language must be capable of consciousness. I defend the latter claim by arguing that a correct understanding of observation sentences requires conscious, sensory experience, (...) and by appealing to the fact that language has meaning in a holistic manner. (shrink)

There is a prevalent notion among cognitive scientists and philosophers of mind that computers are merely formal symbol manipulators, performing the actions they do solely on the basis of the syntactic properties of the symbols they manipulate. This view of computers has allowed some philosophers to divorce semantics from computational explanations. Semantic content, then, becomes something one adds to computational explanations to get psychological explanations. Other philosophers, such as Stephen Stich, have taken a stronger view, advocating doing away with semantics (...) entirely. This paper argues that a correct account of computation requires us to attribute content to computational processes in order to explain which functions are being computed. This entails that computational psychology must countenance mental representations. Since anti-semantic positions are incompatible with computational psychology thus construed, they ought to be rejected. Lastly, I argue that in an important sense, computers are not formal symbol manipulators. (shrink)