Is thinking necessarily linguistic? Do we think with words, to use Bermudez’s (2003) phrase? Or does thinking occur in some other, yet to be determined, representational format? Or again do we think in various formats, switching from one to the other as tasks demand? In virtue perhaps of the ambiguous na- ture of first-person introspective data on the matter, philosophers have tradition- ally disagreed on this question, some thinking that thought had to be pictorial, other insisting that it could not (...) be but linguistic. When any problem divides a community of otherwise intelligent rational thinkers, one suspects some deep conceptual confusion is at play. Indeed, we believe that the conceptual cate- gories used to frame these and related questions are so hopelessly muddled that one could honestly answer “both simultaneously”, or “neither”, depending one what is meant by the alternatives. But let’s get our priorities straight. This paper first and foremost aims at defending what we believe to be a step in that direc- tion of the proper view of thinking, a view we call the spatial-motor view. In order to do so, however, we have found it essential to start by addressing the conceptual confusion just alluded to. Accordingly, the paper proceeds in two steps. First a conceptual step, in which we reconsider some of the traditional categories brought into play when thinking about thinking. Then an empirical step, in which we offer empirical evidence for one of the views conceptually isolated during the first part of the work. Future version of this collaborative work will include a speculative step in which we spin out an evolutionary and developmental scenario whose function it is justify the spatial-motor view by showing how it fits into current evolutionary and developmental theories. (shrink)

Rachlin's view of self-control as a sequence or chain of behaviors is contrasted with traditional behavioral analyses of self-control which emphasize a simplistic interpretation of the hyperbolic function relating small-sooner (SS) and larger-later (LL) reinforcers to specific behaviors. The validity of Rachlin's teleological analysis is examined in relation to the acquisition and steady-state performance of self-control behaviors. Central to an analysis of self-control is the functional difference between behavior under the control of SS and LL reinforcers, because SS-reinforced behavior is (...) more complex due to temporal parameters. (shrink)

The Church–Turing Thesis (CTT) is often employed in arguments for computationalism. I scrutinize the most prominent of such arguments in light of recent work on CTT and argue that they are unsound. Although CTT does nothing to support computationalism, it is not irrelevant to it. By eliminating misunderstandings about the relationship between CTT and computationalism, we deepen our appreciation of computationalism as an empirical hypothesis.

This paper concerns Alan Turing’s ideas about machines, mathematical methods of proof, and intelligence. By the late 1930s, Kurt Gödel and other logicians, including Turing himself, had shown that no finite set of rules could be used to generate all true mathematical statements. Yet according to Turing, there was no upper bound to the number of mathematical truths provable by intelligent human beings, for they could invent new rules and methods of proof. So, the output of a human mathematician, for (...) Turing, was not a computable sequence (i.e., one that could be generated by a Turing machine). Since computers only contained a finite number of instructions (or programs), one might argue, they could not reproduce human intelligence. Turing called this the “mathematical
objection” to his view that machines can think. Logico-mathematical reasons, stemming from his own work, helped to convince Turing that it should be possible to reproduce human intelligence, and eventually compete with it, by developing the appropriate kind of digital computer. He felt it
should be possible to program a computer so that it could learn or discover new rules, overcoming the limitations imposed by the incompleteness and undecidability results in the same way that human
mathematicians presumably do. (shrink)

Self-control is in the eye of the beholder. However, we speak of if a person has come to think conscious thoughts that change the motivational value of stimuli in the outside world. It is claimed that conscious thinking, and not habits bordering on compulsion, is behind self-control.

A thought, taken as a propositional attitude or the content of psychological predicates such as believe, wish, desire, hope, is ascribed to an entity with mental states. A thought is not only allegedly ascribed to particular non-mental things like computer, book, it is also ascribed to non-material things, linguistically in plural terms, e.g. plural pronouns (e.g. we, they), collective names or singular proper names (e.g. the United States), proper names in plural form or general terms (e.g. the Microsoft, feminists). Plural (...) terms are terms referring to groups of entities. The question is - what is it for a group to have a thought? Two main views are currently on centered stage – the literal view and the metaphorical view. This paper argues that the main argument supporting the literal view, in particular Pettit’s view, faces three main problems, namely, the problem of rule-following in propositional coawareness, the problem of an independent verifiability for group beliefs and the problem of the indexical ‘we’- thought. -/- Keywords: thoughts, collective intentionality, social ontology, group agency, group consciousness . (shrink)

The nature of representation has been a central but controversial issue of cognitive philosophy. After 2,500 years of reflection (cf. Rolf 2006), opinions are still divided. On the one hand, there are those who are convinced that we have reached a crisis of representation in the arts, the media, and cultural theory; on the other hand, representation has remained right at the top of the agenda of cognitive science and Artificial Intelligence research (cf. Nöth & Ljungberg, eds. 2003; Nöth 1997). (...) The words in which Daniel Dennett, in 1978, postulates the necessity for a new theory of representation as a foundation of cognitive science are symptomatic of a certain unease about the state of the art: "What is needed is.. (shrink)

The book presents the case that cognitive science should turn its attention to developing theories of human cognition that cover the full range of human perceptual, cognitive, and action phenomena. Cognitive science has now produced a massive number of high-quality regularities with many microtheories that reveal important mechanisms. The need for integration is pressing and will continue to increase. Equally important, cognitive science now has the theoretical concepts and tools to support serious attempts at unified theories. The argument is made (...) entirely by presenting an exemplar unified theory of cognition both to show what a real unified theory would be like and to provide convincing evidence that such theories are feasible. The exemplar is SOAR, a cognitive architecture, which is realized as a software system. After a detailed discussion of the architecture and its properties, with its relation to the constraints on cognition in the real world and to existing ideas in cognitive science, SOAR is used as theory for a wide range of cognitive phenomena: immediate responses ; discrete motor skills ; memory and learning ; problem solving ; language ; and development. The treatments vary in depth and adequacy, but they clearly reveal a single, highly specific, operational theory that works over the entire range of human cognition, SOAR is presented as an exemplar unified theory, not as the sole candidate. Cognitive science is not ready yet for a single theory – there must be multiple attempts. But cognitive science must begin to work toward such unified theories. (shrink)

John Searle has argued that one can imagine embodying a machine running any computer program without understanding the symbols, and hence that purely computational processes do not yield understanding. The disagreement this argument has generated stems, I hold, from ambiguity in talk of 'understanding'. The concept is analysed as a relation between subjects and symbols having two components: a formal and an intentional. The central question, then becomes whether a machine could possess the intentional component with or without the formal (...) component. I argue that the intentional state of a symbol's being meaningful to a subject is a functionally definable relation between the symbol and certain past and present states of the subject, and that a machine could bear this relation to a symbol. I sketch a machine which could be said to possess, in primitive form, the intentional component of understanding. Even if the machine, in lacking consciousness, lacks full understanding, it contributes to a theory of understanding and constitutes a counterexample to the Chinese Room argument. (shrink)

In 1986, I argued that pains are essentially not phenomenal states. Using a Wittgen-steinian son of argument, I showed that the same sort of phenomena can be had on different occasions, and on one occasion persons be in pain, while on another occasion persons not be in pain. I also showed that very different phenomena could be experienced and, yet, organisms have the same sort of pain. I supported my arguments with empirical data from both laboratory and clinical studies. There (...) is nothing about this thesis I would now retract. However, there was a further thesis that needs to be reconsidered. I argued that phenomenal states are only accompaniments of pains, that pains are essentially a combination of cognitive, affective and behavioural/motivational states. This thesis I do now zaish to retract. I now argue that phenomenal states are necessary for pains, but still not sufficient. There must also be a cognitive state which involves an evaluation of the phenomenon as something like, 'Harm to the body'. The evaluation is a kind of de re belief, regarding the phenomenon as itself representing harm to the body. Besides admitting that phenomenal states are necessary for pains, I also now claim that other relevant belief states, affective states, and behavioural/motivational states are not necessary for pain, but normal consequences of pain. This revised theory is preferable to the 1986 one because it fits better with empirical facts (including providing better explanations for anomalous cases), fits better with certain powerful common-sense intuitions, and fits better with a larger theory of consciousness I have been developing. Among other things, it turns out that being in pain is a quite peculiar conscious state and considering it as a paradigm for consciousness is a serious mistake. (shrink)

In mid-twentieth century, the hypothesis, ‘a machine can think’ became very popular after, Alan Turing’s article on ‘Computing Machinery and Intelligence’. This hypothesis, ‘a machine can think’ established the foundations of machine intelligence (MI), and claimed that machines have consciousness and creativity, with the power to compete with human beings. In the first section, I shall show how consciousness and creativity is conceptualized in the domain of MI. The main aim of MI is not only to construct difficult programs to (...) solve our day-to-day problems, but also to reproduce mentality in machines. It was claimed that all the mental qualities are ascribable to machines. My intention in this paper is to clarify consciousness and creativity from a subjective point of view. My claim is that consciousness and creativity cannot be fully represented in a mechanistic domain. There are subjective mental or conscious states, which can be seen in a first-person perspective of their proper understanding. (shrink)

The problem of consciousness is one of the most important problems both in cognitive science and in philosophy. There are different philosophers and different scientists who define consciousness and explain it differently. In philosophy, ‘consciousness’ does not have a definition in terms of genus and differentia or necessary and sufficient conditions. In this paper, I shall explore the very idea of machine consciousness. The machine consciousness has offered causal explanation to the ‘how’ and ‘what’ of consciousness, but they fail to (...) explain the ‘why’ of consciousness. Their explanation is based on the ground that consciousness is causally dependent on the material universe and that of all conscious phenomena can be explained by mapping the physical universe. In this regard, consciousness is basically a physical phenomenon and can be mechanically explained following the naturalistic methods of science. In other words, the mechanistic assumption is that consciousness and mind have an artificial origin and therefore have to be understood only within a mechanistic framework available in the sciences. If this is so, then this epistemological theory of consciousness is essentially committed to scientific world view that cannot avoid metaphysical implication of consciousness. At the same time, neo-Advaitins have maintained that the evolution of nature leads to the manifestation of human consciousness only because consciousness is already implicit in the material nature. Thus, the existence of consciousness in this physical world far exceeds the methods of science and needs a non-mechanical metaphysical explanation. (shrink)

In the mid of nineteenth century, the hypothesis, “machine can think,” became very popular after Alan Turing’s article on “Computing Machinery and Intelligence.” This hypothesis, “machine can think,” established the foundations of machine intelligence and claimed that machines have a mind. It has the power to compete with human beings. In the first section, I shall explore the importance of Turing thesis, which has been conceptualized in the domain of machine intelligence. Turing presented a completely different view of the machine (...) itself. It addressed philosophers, rather than the mathematicians, and proclaimed that digital computers might be considered as intelligent machines. This approach was wholly new, both philosophically and technically, and started many philosophical debates which continue to this day. He proposed an imitation game, as a test, what is now referred to as a Turing test to evaluate if a machine thinks. That is to say that the main aim of machine intelligence not only constructs challenging programs to solve our day-to-day problems but also reproduce mentality in machines and claimed that all the mental qualities are ascribable to machines. What will be attempted in this paper is a critical evaluation of the arguments against the Turing test put forward by many philosophers. (shrink)

You cannot overcome addiction or impulsiveness through abstract patterns alone. They show you the way to go, but do not fuel the effort. Some further variable is needed in the equation, some internal force or motivational mechanism, whatever its nature. Overlooking this leads to a neo-Socratic exaggeration of the role of cognition in selfcontrol.

Many philosophers and psychologists have attempted to elucidate the nature of mental representation by appealing to notions like isomorphism or abstract structural resemblance. The ‘structural representations’ that these theorists champion are said to count as representations by virtue of functioning as internal models of distal systems. In his 2007 book, Representation Reconsidered, William Ramsey endorses the structural conception of mental representation, but uses it to develop a novel argument against representationalism, the widespread view that cognition essentially involves the manipulation of (...) mental representations. Ramsey argues that although theories within the ‘classical’ tradition of cognitive science once posited structural representations, these theories are being superseded by newer theories, within the tradition of connectionism and cognitive neuroscience, which rarely if ever appeal to structural representations. Instead, these theories seem to be explaining cognition by invoking so-called ‘receptor representations’, which, Ramsey claims, aren’t genuine representations at all—despite being called representations, these mechanisms function more as triggers or causal relays than as genuine stand-ins for distal systems. I argue that when the notions of structural and receptor representation are properly explicated, there turns out to be no distinction between them. There only appears to be a distinction between receptor and structural representations because the latter are tacitly conflated with the ‘mental models’ ostensibly involved in offline cognitive processes such as episodic memory and mental imagery. While structural representations might count as genuine representations, they aren’t distinctively mental representations, for they can be found in all sorts of non-intentional systems such as plants. Thus to explain the kinds of offline cognitive capacities that have motivated talk of mental models, we must develop richer conceptions of mental representation than those provided by the notions of structural and receptor representation. (shrink)

Intentionality (‘directedness’, ‘aboutness’) is both a central topic in contemporary philosophy of mind, phenomenology and the cognitive sciences, and one of the themes with which both analytic and Continental philosophers have separately engaged starting from Brentano and Edmund Husserl’s ground-breaking Logical Investigations (1901) through Roderick M. Chisholm, Daniel C. Dennett’s The Intentional Stance, John Searle’s Intentionality, to the recent work of Tim Crane, Robert Brandom, Shaun Gallagher and Dan Zahavi, among many others. In this paper, I shall review recent discussions (...) of intentionality, including some recent explorations of the history of the concept (paying particular attention to Anselm), and suggest some ways the phenomenological approach of Husserl and Heidegger can still offer insights for contemporary philosophy of mind and consciousness. (shrink)

A comment on Paul Schoemaker's target article in Behavioral and Brain Sciences, 14 (1991), p. 205-215, "The Quest for Optimality: A Positive Heuristic of Science?" (https://doi.org/10.1017/S0140525X00066140). This comment argues that the optimizing model of decision leads to an infinite regress, once internal costs of decision (i.e., information and computation costs) are duly taken into account.