According to the dominant computational approach in cognitive science, cognitive agents are digital computers; according to the alternative approach, they are dynamical systems. This target article attempts to articulate and support the dynamical hypothesis. The dynamical hypothesis has two major components: the nature hypothesis (cognitive agents are dynamical systems) and the knowledge hypothesis (cognitive agents can be understood dynamically). A wide range of objections to this hypothesis can be rebutted. The conclusion is that cognitive systems may well be dynamical systems, (...) and only sustained empirical research in cognitive science will determine the extent to which that is true. (shrink)

The notion of a "mental representation" is, arguably, in the first instance a theoretical construct of cognitive science. As such, it is a basic concept of the Computational Theory of Mind, according to which cognitive states and processes are constituted by the occurrence, transformation and storage (in the mind/brain) of information-bearing structures (representations) of one kind or another.

This paper explores a variety of different versions of the thesis that natural language is involved in human thinking. It distinguishes amongst strong and weak forms of this thesis, dismissing some as implausibly strong and others as uninterestingly weak. Strong forms dismissed include the view that language is conceptually necessary for thought (endorsed by many philosophers) and the view that language is _de facto_ the medium of all human conceptual thinking (endorsed by many philosophers and social scientists). Weak forms include (...) the view that language is necessary for the acquisition of many human concepts, and the view that language can serve to scaffold human thought processes. The paper also discusses the thesis that language may be the medium of _conscious_ propositional thinking, but argues that this cannot be its most fundamental cognitive role. The idea is then proposed that natural language is the medium for non-domain-specific thinking, serving to integrate the outputs of a variety of domain-specific conceptual faculties (or central-cognitive ‘quasi-modules’). Recent experimental evidence in support of this idea is reviewed, and the implications of the idea are discussed, especially for our conception of the architecture of human cognition. Finally, some further kinds of evidence which might serve to corroborate or refute the hypothesis are mentioned. The overall goal of the paper is to review a wide variety of accounts of the cognitive function of natural language, integrating a number of different kinds of evidence and theoretical consideration in order to propose and elaborate the most plausible candidate. (shrink)

We survey and clarify some recent appearances of the term ‘emergence’. We distinguish epistemological emergence, which is merely a limitation of descriptive apparatus, from ontological emergence, which should involve causal features of a whole system not reducible to the properties of its parts, thus implying the failure of part/whole reductionism and of mereological supervenience for that system. Are there actually any plausible cases of the latter among the numerous and various mentions of ‘emergence’ in the recent literature? Quantum mechanics seems (...) to offer one, in the Bell properties of entangled particles, but other apparently promising candidates, such as non‐linear dynamical systems investigated by complexity studies and chaos theory, seem on careful analysis to display only epistemological emergence. We examine the consequences for physicalism of admitting ontological emergence in the micro‐physical. (shrink)

Computation and information processing are among the most fundamental notions in cognitive science. They are also among the most imprecisely discussed. Many cognitive scientists take it for granted that cognition involves computation, information processing, or both – although others disagree vehemently. Yet different cognitive scientists use ‘computation’ and ‘information processing’ to mean different things, sometimes without realizing that they do. In addition, computation and information processing are surrounded by several myths; first and foremost, that they are the same thing. In (...) this paper, we address this unsatisfactory state of affairs by presenting a general and theory-neutral account of computation and information processing. We also apply our framework by analyzing the relations between computation and information processing on one hand and classicism and connectionism on the other. We defend the relevance to cognitive science of both computation, in a generic sense that we fully articulate for the first time, and information processing, in three important senses of the term. Our account advances some foundational debates in cognitive science by untangling some of their conceptual knots in a theory-neutral way. By leveling the playing field, we pave the way for the future resolution of the debates’ empirical aspects. (shrink)

The historical debate on representation in cognitive science and neuroscience construes representations as theoretical posits and discusses the degree to which we have reason to posit them. We reject the premise of that debate. We argue that experimental neuroscientists routinely observe and manipulate neural representations in their laboratory. Therefore, neural representations are as real as neurons, action potentials, or any other well-established entities in our ontology.

Laws of nature take center stage in philosophy of science. Laws are usually believed to stand in a tight conceptual relation to many important key concepts such as causation, explanation, confirmation, determinism, counterfactuals etc. Traditionally, philosophers of science have focused on physical laws, which were taken to be at least true, universal statements that support counterfactual claims. But, although this claim about laws might be true with respect to physics, laws in the special sciences (such as biology, psychology, economics etc.) (...) appear to have—maybe not surprisingly—different features than the laws of physics. Special science laws—for instance, the economic law “Under the condition of perfect competition, an increase of demand of a commodity leads to an increase of price, given that the quantity of the supplied commodity remains constant” and, in biology, Mendel's Laws—are usually taken to “have exceptions”, to be “non-universal” or “to be ceteris paribus laws”. How and whether the laws of physics and the laws of the special sciences differ is one of the crucial questions motivating the debate on ceteris paribus laws. Another major, controversial question concerns the determination of the precise meaning of “ceteris paribus”. Philosophers have attempted to explicate the meaning of ceteris paribus clauses in different ways. The question of meaning is connected to the problem of empirical content, i.e., the question whether ceteris paribus laws have non-trivial and empirically testable content. Since many philosophers have argued that ceteris paribus laws lack empirically testable content, this problem constitutes a major challenge to a theory of ceteris paribus laws. (shrink)

A comprehensive introduction to the Language of Though Hypothesis (LOTH) accessible to general audiences. LOTH is an empirical thesis about thought and thinking. For their explication, it postulates a physically realized system of representations that have a combinatorial syntax (and semantics) such that operations on representations are causally sensitive only to the syntactic properties of representations. According to LOTH, thought is, roughly, the tokening of a representation that has a syntactic (constituent) structure with an appropriate semantics. Thinking thus consists in (...) syntactic operations defined over representations. Most of the arguments for LOTH derive their strength from their ability to explain certain empirical phenomena like productivity, systematicity of thought and thinking. (shrink)

Mind &Language, Volume 35, Issue 1, Page 90-114, February 2020.

According to the received view in philosophy of mind, mental states or properties are _realized_ by brain states or properties but are not identical to them. This view is often called _realization_ _physicalism_. Carl Gillett has recently defended a detailed formulation of the realization relation. However, Gillett’s formulation cannot be the relation that realization physicalists have in mind. I argue that Gillett’s “dimensioned” view of realization fails to apply to a textbook case of realization. I also argue Gillett counts as (...) realization some cases that should not count if realization physicalism is to be distinguished from its competitors in the usual ways. I conclude that the relation described by Gillett cannot be realization. (shrink)

The question, ‘Is cognition linguistic?' divides recent cognitive theories into two antagonistic groups. Sententialists claim that we think in some language, while advocates of non linguistic views of cognition deny this claim. The Introspective Argument for Sententialism is one of the most appealing arguments for sententialism. In substance, it claims that the introspective fact of inner speech provides strong evidence that our thoughts are linguistic. This article challenges this argument. I claim that the Introspective Argument for Sententialism confuses the content (...) of our thoughts with their vehicles: while sententialism is a thesis about the vehicles of our thoughts, inner speech sentences are the content of auditory or articulatory images. The rebuttal of the introspective argument for sententialism is shown to have a general significance in cognitive science: Introspection does not tell us how we think. (shrink)

Advocates of dynamic systems have suggested that higher mental processes are based on continuous representations. In order to evaluate this claim, we first define the concept of representation, and rigorously distinguish between discrete representations and continuous representations. We also explore two important bases of representational content. Then, we present seven arguments that discrete representations are necessary for any system that must discriminate between two or more states. It follows that higher mental processes require discrete representations. We also argue that discrete (...) representations are more influenced by conceptual role than continuous representations. We end by arguing that the presence of discrete representations in cognitive systems entails that computationalism (i.e., the view that the mind is a computational device) is true, and that cognitive science should embrace representational pluralism. (shrink)

David Marr provided a useful framework for theorizing about cognition within classical, AI-style cognitive science, in terms of three levels of description: the levels of (i) cognitive function, (ii) algorithm and (iii) physical implementation. We generalize this framework: (i) cognitive state transitions, (ii) mathematical/functional design and (iii) physical implementation or realization. Specifying the middle, design level to be the theory of dynamical systems yields a nonclassical, alternative framework that suits (but is not committed to) connectionism. We consider how a brain's (...) (or a network's) being a dynamical system might be the key both to its realizing various essential features of cognition — productivity, systematicity, structure-sensitive processing, syntax — and also to a non-classical solution of (frame-type) problems plaguing classical cognitive science. (shrink)

In computational complexity theory, decision problems are divided into complexity classes based on the amount of computational resources it takes for algorithms to solve them. In theoretical computer science, it is commonly accepted that only functions for solving problems in the complexity class P, solvable by a deterministic Turing machine in polynomial time, are considered to be tractable. In cognitive science and philosophy, this tractability result has been used to argue that only functions in P can feasibly work as computational (...) models of human cognitive capacities. One interesting area of computational complexity theory is descriptive complexity, which connects the expressive strength of systems of logic with the computational complexity classes. In descriptive complexity theory, it is established that only first-order (classical) systems are connected to P, or one of its subclasses. Consequently, second-order systems of logic are considered to be computationally intractable, and may therefore seem to be unfit to model human cognitive capacities. This would be problematic when we think of the role of logic as the foundations of mathematics. In order to express many important mathematical concepts and systematically prove theorems involving them, we need to have a system of logic stronger than classical first-order logic. But if such a system is considered to be intractable, it means that the logical foundation of mathematics can be prohibitively complex for human cognition. In this paper I will argue, however, that this problem is the result of an unjustified direct use of computational complexity classes in cognitive modelling. Placing my account in the recent literature on the topic, I argue that the problem can be solved by considering computational complexity for humanly relevant problem solving algorithms and input sizes. (shrink)

According to rationalism regarding the psychology of moral judgment, people’s moral judgments are generally the result of a process of reasoning that relies on moral principles or rules. By contrast, intuitionist models of moral judgment hold that people generally come to have moral judgments about particular cases on the basis of gut-level, emotion-driven intuition, and do so without reliance on reasoning and hence without reliance on moral principles. In recent years the intuitionist model has been forcefully defended by Jonathan Haidt. (...) One important implication of Haidt’s model is that in giving reasons for their moral judgments people tend to confabulate – the reasons they give in attempting to explain their moral judgments are not really operative in producing those judgments. Moral reason-giving on Haidt’s view is generally a matter of post hoc confabulation. Against Haidt, we argue for a version of rationalism that we call ‘morphological rationalism.’ We label our version ‘morphological’ because according to it, the information contained in moral principles is embodied in the standing structure of a typical individual’s cognitive system, and this morphologically embodied information plays a causal role in the generation of particular moral judgments. The manner in which the principles play this role is via ‘proceduralization’ – such principles operate automatically. In contrast to Haidt’s intuitionism, then, our view does not imply that people’s moral reason-giving practices are matters of confabulation. In defense of our view, we appeal to what we call the ‘nonjarring’ character of the phenomenology of making moral judgments and of giving reasons for those judgments. (shrink)

Following Marr’s famous three-level distinction between explanations in cognitive science, it is often accepted that focus on modeling cognitive tasks should be on the computational level rather than the algorithmic level. When it comes to mathematical problem solving, this approach suggests that the complexity of the task of solving a problem can be characterized by the computational complexity of that problem. In this paper, I argue that human cognizers use heuristic and didactic tools and thus engage in cognitive processes that (...) make their problem solving algorithms computationally suboptimal, in contrast with the optimal algorithms studied in the computational approach. Therefore, in order to accurately model the human cognitive tasks involved in mathematical problem solving, we need to expand our methodology to also include aspects relevant to the algorithmic level. This allows us to study algorithms that are cognitively optimal for human problem solvers. Since problem solving methods are not universal, I propose that they should be studied in the framework of enculturation, which can explain the expected cultural variance in the humanly optimal algorithms. While mathematical problem solving is used as the case study, the considerations in this paper concern modeling of cognitive tasks in general. (shrink)

In this paper, I outline two strands of evidence for the conclusion that the dynamical approach to cognitive science both seeks and provides covering law explanations. Two of the most successful dynamical models—Kelso’s model of rhythmic finger movement and Thelen et al.’s model of infant perseverative reaching—can be seen to provide explanations which conform to the famous explanatory scheme first put forward by Hempel and Oppenheim. In addition, many prominent advocates of the dynamical approach also express the provision of this (...) kind of explanation as a goal of dynamical cognitive science. I conclude by briefly outlining two consequences. First, dynamical cognitive science’s explanatory style may strengthen its links to the so-called “situated” approach to cognition, but, secondly, it may also undermine the widespread intuition that dynamics is related to emergentism in the philosophy of mind. (shrink)

One of the central points of contention in the epistemology of testimony concerns the uniqueness (or not) of the justification of beliefs formed through testimony--whether such justification can be accounted for in terms of, or 'reduced to,' other familiar sort of justification, e.g. without relying on any epistemic principles unique to testimony. One influential argument for the reductionist position, found in the work of Elizabeth Fricker, argues by appeal to the need for the hearer to monitor the testimony for credibility. (...) Fricker (1994) argues, first, that some monitoring for trustworthiness is required if the hearer is to avoid being gullible, and second, that reductionism but not anti-reductionism is compatible with ascribing an important role to the process of monitoring in the course of justifiably accepting observed testimony. In this paper we argue that such an argument fails. (shrink)

This paper surveys and evaluates the answers that philosophers and animal researchers have given to two questions. Do animals have thoughts? If so, are their thoughts conceptual? Along the way, special attention is paid to distinguish debates of substance from mere battles over terminology, and to isolate fruitful areas for future research.

Showcasing original arguments for well-defined positions, as well as clear and concise statements of sophisticated philosophical views, this volume is an ...

This paper presents the leading idea of my doctoral dissertation and thus has been shaped by the reactions of all the members of my thesis committee: Charles Chastain, Walter Edelberg, W. Kent Wilson, Dorothy Grover, and Charles Marks. I am especially grateful for the help of Professors Chastain, Edelberg, and Wilson; each worked closely with me at one stage or another in the development of the ideas contained in the present work. Shorter versions of this paper were presented at the (...) 47th Annual Northwest Conference on Philosophy (1995), the 1996 Mid-South Philosophy Conference, the 1997 meeting of the Central Division of the American Philosophical Association, and at the University of Washington, Seattle; thanks to all audiences for their insightful comments and questions and also to my conference commentators, Eric Gampel, Jonathan Cohen, and Bruce Glymour, respectively, each of whom offered a thoughtful critique. Lastly, I extend my gratitude to anonymous referees, including two from Mind and Language, whose remarks led to significant improvements in the paper. Address for correspondence: 13416, 4th Ave. S., Seattle, WA 98168, USA E-mail: [email protected].. (shrink)

Traditionally, the language faculty was supposed to be a device that maps linguistic inputs to semantic or conceptual representations. These representations themselves were supposed to be distinct from the representations manipulated by the hearer’s perceptual and motor systems. Recently this view of language has been challenged by advocates of embodied cognition. Drawing on empirical studies of linguistic comprehension, they have proposed that the language faculty reuses the very representations and processes deployed in perceiving and acting. I review some of the (...) evidence and arguments in favor of the embodied view of language comprehension, and argue that none of it is conclusive. Moreover, the embodied view itself blurs two important distinctions: first, the distinction between linguistic comprehension and its typical consequences; and second, the distinction between representational content and vehicles. Given that these distinctions are well-motivated, we have good reason to reject the embodied view of linguistic understanding.Keywords: Language; Comprehension; Perception; Action; Embodied cognition; Representation. (shrink)

, Pietroski and Rey ([1995]) suggested a reconstruction of ceteris paribus (CP)-laws, which — as they claim — saves CP-laws from vacuity. This discussion note is intended to show that, although Pietroski and Rey's reconstruction is an improvement in comparison to previous suggestions, it cannot avoid the result that CP-laws are almost vacuous. It is proved that if Cx is an arbitrary (nomological) event-type which has independently identifiable deterministic causes, then for every other (nomological) event-type Ax which is not strictly (...) connected with Cx or with ¬Cx, ‘CP if Ax then Cx’ satisfies the conditions of Pietroski and Rey for CP-laws. It is also shown that Pietroski and Rey's reconstruction presupposes the assumption of determinism. The conclusion points towards some alternatives to Piectroski and Rey's reconstruction. (shrink)

Morphological content is information that is implicitly embodied in the standing structure of a cognitive system and is automatically accommodated during cognitive processing without first becoming explicit in consciousness. We maintain that much belief-formation in human cognition is essentially morphological : i.e., it draws heavily on large amounts of morphological content, and must do so in order to tractably accommodate the holistic evidential relevance of background information possessed by the cognitive agent. We also advocate a form of experiential evidentialism concerning (...) epistemic justification—roughly, the view that the justification-status of an agent’s beliefs is fully determined by the character of the agent’s conscious experience. We have previously defended both the thesis that much belief-formation is essentially morphological, and also a version of evidentialism. Here we explain how experiential evidentialism can be smoothly and plausibly combined with the thesis that much of the cognitive processing that generates justified beliefs is essentially morphological. The leading idea is this: even though epistemically relevant morphological content does not become explicit in consciousness during the process of belief-generation, nevertheless such content does affect the overall character of conscious experience in an epistemically significant way: it is implicit in conscious experience, and is implicitly appreciated by the experiencing agent. (shrink)

Over the past thirty years, it is been common to hear the mind likened to a digital computer. This essay is concerned with a particular philosophical view that holds that the mind literally is a digital computer (in a specific sense of “computer” to be developed), and that thought literally is a kind of computation. This view—which will be called the “Computational Theory of Mind” (CTM)—is thus to be distinguished from other and broader attempts to connect the mind with computation, (...) including (a) various enterprises at modeling features of the mind using computational modeling techniques, and (b) employing some feature or features of production-model computers (such as the stored program concept, or the distinction between hardware and software) merely as a guiding metaphor for understanding some feature of the mind. This entry is therefore concerned solely with the Computational Theory of Mind (CTM) proposed by Hilary Putnam [1961] and developed most notably for philosophers by Jerry Fodor [1975, 1980, 1987, 1993]. The senses of ‘computer’ and ‘computation’ employed here are technical; the main tasks of this entry will therefore be to elucidate: (a) the technical sense of ‘computation’ that is at issue, (b) the ways in which it is claimed to be applicable to the mind, (c) the philosophical problems this understanding of the mind is claimed to solve, and (d) the major criticisms that have accrued to this view. (shrink)

While the research programs in early cognitive science and artificial intelligence aimed to articulate what cognition was in ideal terms, much research in contemporary computational neuroscience looks at how and why brains fail to function as they should ideally. This focus on impairment affects how we understand David Marr's hypothesized three levels of understanding. In this essay, we suggest some refinements to Marr's distinctions using a population activity model of cortico-striatal circuitry exploring impulsivity and behavioral inhibition as a case study. (...) In particular, we urge that Marr's computational level should be redefined to include a description of how systems break down. We also underscore that feed-forward processing, cognition disconnected from behavioral context, and representations do not always drive cognition in the way that Marr originally assumed. (shrink)

This study addresses the dynamical nature of a “representation‐hungry” cognitive task involving an imagined action. In our experiment, participants were handed rods that systematically increased or decreased in length on subsequent trials. Participants were asked to judge whether or not they thought they could reach for a distant object with the hand‐held rod. The results are in agreement with a dynamical model, extended from Tuller, Case, Ding, and Kelso (1994). The dynamical effects observed in this study suggest that predictive judgments (...) regarding the possibility or impossibility of a certain action can be understood in terms of dynamically evolving basins of attraction instead of as depending on representational structures. (shrink)

Within cognitive science, mental processing is often construed as computation over mental representations—i.e., as the manipulation and transformation of mental representations in accordance with rules of the kind expressible in the form of a computer program. This foundational approach has encountered a long-standing, persistently recalcitrant, problem often called the frame problem; it is sometimes called the relevance problem. In this paper we describe the frame problem and certain of its apparent morals concerning human cognition, and we argue that these morals (...) have significant import regarding both the nature of moral normativity and the human capacity for mastering moral normativity. The morals of the frame problem bode well, we argue, for the claim that moral normativity is not fully systematizable by exceptionless general principles, and for the correlative claim that such systematizability is not required in order for humans to master moral normativity. (shrink)

Section 1 of the paper reviews a family of “no good inference” arguments for skepticism about the external world, and a straightforward externalist reply. Section 2 reviews skeptical regress arguments, and another straightforward reply. Section 3 considers three objections to foundationalism that are inspired by Sellars’ critique of “the given” in “Empiricism and the Philosophy of Mind,” and argues that none of these is effective against the kind of “externalist foundationalism” defended in Sects. 1 and 2.

We propose an approach to epistemic justification that incorporates elements of both reliabilism and evidentialism, while also transforming these elements in significant ways. After briefly describing and motivating the non-standard version of reliabilism that Henderson and Horgan call “transglobal” reliabilism, we harness some of Henderson and Horgan’s conceptual machinery to provide a non-reliabilist account of propositional justification (i.e., evidential support). We then invoke this account, together with the notion of a transglobally reliable belief-forming process, to give an account of doxastic (...) justification. (shrink)

Naturalistically minded philosophers hope to identify a privileged nonsemantic relation that holds between a mental representation m and that which m represents, a relation whose privileged status underwrites the assignment of reference to m. The naturalist can accomplish this task only if she has in hand a nonsemantic criterion for individuating mental representations: it would be question-begging for the naturalist to characterize m, for the purpose of assigning content, as 'the representation with such and such content'. If we individuate mental (...) representations using the tools of dynamical systems theory, we find that a given mental representation, characterized nonsemantically, emerges in the cognitive system as the result of causal interactions between the subject and her environment. At least for the most basic of our mental representations, I argue that the dynamical systems-based approach to individuation increases the plausibility of a theory that assigns reference as a function of the subject's causal history. (shrink)

The ‘received view’ of the analog–digital distinction holds that analog representations are continuous while digital representations are discrete. In this paper I first provide support for the received view by showing how it (1) emerges from the theory of computation, and (2) explains engineering practices. Second, I critically assess several recently offered alternatives, arguing that to the degree they are justified they demonstrate not that the received view is incorrect, but rather that distinct senses of the terms have become entrenched (...) specific fields, perhaps most notably in the cognitive psychology of mental imagery. (shrink)

In Connectionism and the Philosophy of Psychology, Horgan and Tienson (1996) argue that cognitive processes, pace classicism, are not governed by exceptionless, “representation-level” rules; they are instead the work of defeasible cognitive tendencies subserved by the non-linear dynamics of the brain’s neural networks. Many theorists are sympathetic with the dynamical characterisation of connectionism and the general (re)conception of cognition that it affords. But in all the excitement surrounding the connectionist revolution in cognitive science, it has largely gone unnoticed that connectionism (...) adds to the traditional focus on computational processes, a new focus – one on the vehicles of mental representation, on the entities that carry content through the mind. Indeed, if Horgan and Tienson’s dynamical characterisation of connectionism is on the right track, then so intimate is the relationship between computational processes and representational vehicles, that connectionist cognitive science is committed to a resemblance theory of mental content. (shrink)

Cognitive neuroscientists are turning to an increasingly rich array of neurodynamical systems to explain mental phenomena. In these explanations, cognitive capacities are decomposed into a set of functions, each of which is described mathematically, and then these descriptions are mapped on to corresponding mathematical descriptions of the dynamics of neural systems. In this paper, I outline a novel explanatory schema based on these explanations. I then argue that these explanations present a novel type of dynamicism for the philosophy of mind (...) and neuroscience, componential dynamicism, that focuses on the parts of cognitive systems that fill certain functional roles in producing cognitive phenomena. (shrink)

The paper argues that cognitive states of biological systems are inherently temporal. Three adequacy conditions for neuronal models of representation are vindicated: the compositionality of meaning, the compositionality of content, and the co-variation with content. Classicist and connectionist approaches are discussed and rejected. Based on recent neurobiological data, oscillatory networks are introduced as a third alternative. A mathematical description in a Hilbert space framework is developed. The states of this structure can be regarded as conceptual representations satisfying the three conditions.

This study addresses the dynamical nature of a “representation‐hungry” cognitive task involving an imagined action. In our experiment, participants were handed rods that systematically increased or decreased in length on subsequent trials. Participants were asked to judge whether or not they thought they could reach for a distant object with the hand‐held rod. The results are in agreement with a dynamical model, extended from Tuller, Case, Ding, and Kelso (1994). The dynamical effects observed in this study suggest that predictive judgments (...) regarding the possibility or impossibility of a certain action can be understood in terms of dynamically evolving basins of attraction instead of as depending on representational structures. (shrink)

The recent move to naturalize phenomenology through a mathematical protocol is a significant advance in consciousness research. It enables a new and fruitful level of dialogue between the cognitive sciences and phenomenology of such a nuanced kind that it also prompts advancement in our phenomenological analyses. But precisely what is going on at this point of ‘dialogue’ between phenomenological descriptions and mathematical algorithms, the latter of which are based on dynamical systems theory? It will be shown that what is happening (...) is something more than a mere ‘passing of the baton’ from phenomenology to mathematics. For this sophisticated naturalization to prove a worthy endeavour it must produce more than just correlation, it must prove some form of interrelation to the extent that phenomenology is deterministic. But such interrelational and deterministic requirements are the start of a slippery slope, and it will be argued that this slope only loses more friction once a further demand of formal and precise descriptions is made of phenomenology. Such deterministic and formally precise demands misconstrue phenomenology’s ideal goal of a unification of genuine/originary reason and truth. Not a deductive and definitive discipline, phenomenology is rather from the outset descriptive and critical. Phenomenology’s descriptive beginnings will thus be employed as an essential barrier to the naturalization of phenomenology. (shrink)

This paper explores the nature of self-knowledge of beliefs by investigating the relationship between self-knowledge of beliefs and one's knowledge of other people's beliefs. It introduces and defends a new account of self-knowledge of beliefs according to which this type of knowledge is developmentally interconnected with and dependent on resources already used for acquiring knowledge of other people's beliefs, which is inferential in nature. But when these resources are applied to oneself, one attains and subsequently frequently uses a method for (...) acquiring knowledge of beliefs that is non-inferential in nature. The paper argues that this account is preferable to some of the most common empirically motivated theories of self-knowledge of beliefs and explains the origin of the widely discussed phenomenon that our own beliefs are often transparent to us in that we can determine whether we believe that p simply by settling whether p is the case. (shrink)

It seems that hope springs eternal for the cherished idea that norms (or normativeprinciples) explain actions or regularities in actions. But it also seems thatthere are many ways of going wrong when taking norms and normative principlesas explanatory. The author argues that neither norms nor normative principles—insofar as they are the sort of things with normative force—is explanatoryof what is done. He considers the matter using both erotetic and ontic models ofexplanation. He further considers various understandings of norms. Key Words: (...) explanation • norms • social science • rationality. (shrink)

. Interpreted dynamical systems are dynamical systems with an additional interpretation mapping by which propositional formulas are assigned to system states. The dynamics of such systems may be described in terms of qualitative laws for which a satisfaction clause is defined. We show that the systems Cand CL of nonmonotonic logic are adequate with respect to the corresponding description of the classes of interpreted ordered and interpreted hierarchical systems, respectively. Inhibition networks, artificial neural networks, logic programs, and evolutionary systems are (...) instances of such interpreted dynamical systems, and thus our results entail that each of them may be described correctly and, in a sense, even completely by qualitative laws that obey the rules of a nonmonotonic logic system. (shrink)

The past decade has witnessed the emergence of a novel stance on semantic representation, and its relationship to context sensitivity. Connectionist-minded philosophers, including Clark and van Gelder, have espoused the merits of viewing hidden-layer, context-sensitive representations as possessing semantic content, where this content is partially revealed via the representations'' position in vector space. In recent work, Bodén and Niklasson have incorporated a variant of this view of semantics within their conception of semantic systematicity. Moreover, Bodén and Niklasson contend that they (...) have produced experimental results which not only satisfy a kind of context-based, semantic systematicity, but which, to the degree that reality permits, effectively deals with challenges posed by Fodor and Pylyshyn (1988), and Hadley (1994a). The latter challenge involved well-defined criteria for strong semantic systematicity. This paper examines the relevant claims and experiments of Bodén and Niklasson. It is argued that their case fatally involves two fallacies of equivocation; one concerning ''semantic content'' and the other concerning ''novel test sentences''. In addition, it is argued that their ultimate construal of context sensitive semantics contains serious confusions. These confusions are also found in certain publications dealing with "latent semantic analysis". Thus, criticisms presented here have relevance beyond the work of Bodén and Niklasson. (shrink)

Recently, connectionist models have been developed that seem to exhibit structuresensitive cognitive capacities without executing a program. This paper examines one such model and argues that it does execute a program. The argument proceeds by showing that what is essential to running a program is preserving the functional structure of the program. It has generally been assumed that this can only be done by systems possessing a certain temporalcausal organization. However, counterfactualpreserving functional architecture can be instantiated in other ways, for (...) example geometrically, which are realizable by connectionist networks. (shrink)

While Process Reliabilism has long been regarded by many as a version of Foundationalism, this paper argues that there is a version of Process Reliabilism that can also been seen as at least a partial vindication of Coherentism as well. The significance of this result lies in what it tells us both about the prospects for a plausible Process Reliabilism, but also about the old-school debate between Foundationalists and Coherentists.

We sketch the view we call contextual semantics. It asserts that truth is semantically correct affirmability under contextually variable semantic standards, that truth is frequently an indirect form of correspondence between thought/language and the world, and that many Quinean commitments are not genuine ontological commitments. We argue that contextualist semantics fits very naturally with the view that the pertinent semantic standards are particularist rather than being systematizable as exceptionless general principles.

One of the best known arguments against the connectionist approach to artificial intelligence and cognitive science is that neural networks are black boxes, i.e., there is no understandable account of their operation. This difficulty has impeded efforts to explain how categories arise from raw sensory data. Moreover, it has complicated investigation about the role of symbols and language in cognition. This state of things has been radically changed by recent experimental findings in artificial deep learning research. Two kinds of artificial (...) deep learning networks, namely the convolutional neural network and the generative adversarial network have been found to possess the capability to build internal states that are interpreted by humans as complex visual categories, without any specific hints or any grammatical processing. This emergent ability suggests that those categories do not depend on human knowledge or the syntactic structure of language, while they do rely on their visual context. This supports a mild form of empiricism, while it does not assume that computational functionalism is true. Some consequences are extracted regarding the debate about amodal and grounded representations in the human brain. Furthermore, new avenues for research on cognitive science are open. (shrink)

Traditional approaches to modeling cognitive systems are computational, based on utilizing the standard tools and concepts of the theory of computation. More recently, a number of philosophers have argued that cognition is too subtle or complex for these tools to handle. These philosophers propose an alternative based on dynamical systems theory. Proponents of this view characterize dynamical systems as (i) utilizing continuous rather than discrete mathematics, and, as a result, (ii) being computationally more powerful than traditional computational automata. Indeed, the (...) logical possibility of such super-powerful systems has been demonstrated in the form of analog artificial neural networks. In this paper I consider three arguments against the nomological possibility of these automata. While the first two arguments fail, the third succeeds. In particular, the presence of noise reduces the computational power of analog networks to that of traditional computational automata, and noise is a pervasive feature of information processing in biological systems. Consequently, as an empirical thesis, the proposed dynamical alternative is under-motivated: What is required is an account of how continuously valued systems could be realized in physical systems despite the ubiquity of noise. (shrink)