This entry provides an overview of theories of concepts that is organized around five philosophical issues: (1) the ontology of concepts, (2) the structure of concepts, (3) empiricism and nativism about concepts, (4) concepts and natural language, and (5) concepts and conceptual analysis.

Some recent cognitive-scientific research suggests that a considerable amount of intelligent action is generated not by the systematic activity of internal representations, but by complex interactions involving neural, bodily, and environmental factors. Following an analysis of this threat to representational explanation, we pursue an analogy between the role of genes in the production of biological form and the role of neural states in the production of behaviour, in order to develop a notion of genic representation. In both cases an appeal (...) to normal ecological context is used to balance multi-factoral, interactive causal determination against the intuition that certain aspects of the causal nexus play a special role in promoting adaptive success. Certain worries abut this vision help us to get a better grip on the concept of genic representation itself. We end with a puzzle concerning the relation between cognition and representation. (shrink)

The philosophical technical term "supervenience" is frequently used in the philosophy of mind as a concise way of characterizing the core idea of physicalism in a manner that is neutral with respect to debates between reductive physicalists and nonreductive physicalists. I argue against this alleged neutrality and side with reductive physicalists. I am especially interested here in debates between psychoneural reductionists and nonreductive functionalist physicalists. Central to my arguments will be considerations concerning how best to articulate the spirit of the (...) idea of supervenience. I argue for a version of supervenience, "fine-grained supervenience," which is the claim that if, at a given time, a single entity instantiates two distinct mental properties, it must do so in virtue of instantiating two distinct physical properties. I argue further that despite initial appearances to the contrary, such a construal of supervenience can be embraced only by reductive physicalists. (shrink)

Review of: Margaret A. Boden, Mind as Machine: A History of Cognitive Science, 2 vols, Oxford: Oxford University Press, 2006, xlvii+1631, cloth $225, ISBN 0-19-924144-9. - Mind as Machine is Margaret Boden’s opus magnum. For one thing, it comes in two massive volumes of nearly 1700 pages, ... But it is not just the opus magnum in simple terms of size, but also a truly crowning achievement of half a century’s career in cognitive science.

The paper presents and discusses the “which-is-which content of handedness,” the meaning of left as left and right as right, as a possible candidate for the idea of a genuine embodied cognitive content. After showing that the Ozma barrier, the non-transferability of the meaning of left and right, provides a kind of proof of the non-descriptive, indexical nature of the which-is-which content of handedness, arguments are presented which suggest that the classical representationalist account of cognition faces a perplexing problem of (...) underdetermination of reference of left and right in the which-is-which sense. By way of contrast, no such problems occur in a framework were embodied contents are not mediated by some extra body model which carries the representational power, but are instead directly represented. (shrink)

Since the early eighties, computationalism in the study of the mind has been “under attack” by several critics of the so-called “classic” or “symbolic” approaches in AI and cognitive science. Computationalism was generically identified with such approaches. For example, it was identified with both Allen Newell and Herbert Simon’s Physical Symbol System Hypothesis and Jerry Fodor’s theory of Language of Thought, usually without taking into account the fact ,that such approaches are very different as to their methods and aims. Zenon (...) Pylyshyn, in his influential book Computation and Cognition, claimed that both Newell and Fodor deeply influenced his ideas on cognition as computation. This probably added to the confusion, as many people still consider Pylyshyn’s book as paradigmatic of the computational approach in the study of the mind. Since then, cognitive scientists, AI researchers and also philosophers of the mind have been asked to take sides on different “paradigms” that have from time to time been proposed as opponents of (classic or symbolic) computationalism. Examples of such oppositions are: -/- computationalism vs. connectionism, computationalism vs. dynamical systems, computationalism vs. situated and embodied cognition, computationalism vs. behavioural and evolutionary robotics. -/- Our preliminary claim in section 1 is that computationalism should not be identified with what we would call the “paradigm (based on the metaphor) of the computer” (in the following, PoC). PoC is the (rather vague) statement that the mind functions “as a digital computer”. Actually, PoC is a restrictive version of computationalism, and nobody ever seriously upheld it, except in some rough versions of the computational approach and in some popular discussions about it. Usually, PoC is used as a straw man in many arguments against computationalism. In section 1 we look in some detail at PoC’s claims and argue that computationalism cannot be identified with PoC. In section 2 we point out that certain anticomputationalist arguments are based on this misleading identification. In section 3 we suggest that the view of the levels of explanation proposed by David Marr could clarify certain points of the debate on computationalism. In section 4 we touch on a controversial issue, namely the possibility of developing a notion of analog computation, similar to the notion of digital computation. A short conclusion follows in section 5. (shrink)

A case study in historical cognitive science, this paper addresses two claims made by radical proponents of new dynamical approaches. It queries their historical narrative, which sees embodied, situated cognition as correcting an individualist, atemporal framework originating in Descartes. In fact, new Descartes scholarship shows that 17th-century animal spirits neurophysiology realized a recognizably distributed model of memory; explicit representations are patterns of spirit flow, and memory traces are changes left by experience in connections between brain pores. This historical sketch supports (...) the second dynamicist claim, that connectionists' stress on the cognitive importance of pattern-recreation needs supplementing by dynamicists' real-time focus and attention to the active roles of body and environment. Animal spirits theory exhibits just the 'continuous reciprocal causation' between brain, body, and environment which Andy Clark sees as dynamicism's central contribution, and allows for the embedding of brains in culture as well as the physical world. (shrink)

The last ten years have seen an increasing interest, within cognitive science, in issues concerning the physical body, the local environment, and the complex interplay between neural systems and the wider world in which they function. --œPhysically embodied, environmentally embedded--� approaches thus loom large on the contemporary cognitive scientific scene. Yet many unanswered questions remain, and the shape of a genuinely embodied, embedded science of the mind is still unclear. I begin by sketching a few examples of the approach, and (...) then raise a variety of critical questions concerning its nature and scope. A distinction is drawn between two kinds of appeal to embodiment: 'simple' cases, in which bodily and environmental properties merely constrain accounts that retain the focus on inner organization and processing, and more radical appeals, in which attention to bodily and environmental features is meant to transform both the subject matter and the theoretical framework of cognitive science. (shrink)

In the past decade, the notion of a neural correlate of consciousness (or NCC) has become a focal point for scientific research on consciousness (Metzinger, 2000a). A growing number of investigators believe that the first step toward a science of consciousness is to discover the neural correlates of consciousness. Indeed, Francis Crick has gone so far as to proclaim that ‘we … need to discover the neural correlates of consciousness.… For this task the primate visual system seems especially attractive.… No (...) longer need one spend time attempting … to endure the tedium of philosophers perpetually disagreeing with each other. Con- sciousness is now largely a scientific problem’ (Crick, 1996, p. 486).2 Yet the question of what it means to be a neural correlate of consciousness is actually far from straightforward, for it involves fundamental empirical, methodological, and _philosophical _issues about the nature of consciousness and its relationship to the brain. Even if one assumes, as we do, that states of consciousness causally depend on states of the brain, one can nevertheless wonder in what sense there is, or could be, such a thing as a neural correlate of consciousness. (shrink)

The nature of the dynamical hypothesis in cognitive science (the DH) is further clarified in responding to various criticisms and objections raised in commentaries. Major topics addressed include the definitions of “dynamical system” and “digital computer;” the DH as Law of Qualitative Structure; the DH as an ontological claim; the multiple-realizability of dynamical models; the level at which the DH is pitched; the nature of dynamics; the role of representations in dynamical cognitive science; the falsifiability of the DH; the extent (...) to which the DH is open; the role of temporal and implementation considerations; and the novelty or importance of the DH. The basic formulation and defense of the DH in the target article survives intact, though some refinements are recommended. (shrink)

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)

Van Gelder (1995) has recently spearheaded a movement to challenge the dominance of connectionist and classicist models in cognitive science. The dynamical conception of cognition is van Gelder's replacement for the computation bound paradigms provided by connectionism and classicism. He relies on the Watt governor to fulfill the role of a dynamicist Turing machine and claims that the Motivational Oscillatory Theory (MOT) provides a sound empirical basis for dynamicism. In other words, the Watt governor is to be the theoretical exemplar (...) of the class of systems necessary for cognition and MOT is an empirical instantiation of that class. However, I shall argue that neither the Watt governor nor MOT successfully fulfill these prescribed roles. This failure, along with van Gelder's peculiar use of the concept of computation and his struggle with representationalism, prevent him from providing a convincing alternative to current cognitive theories. (shrink)

The purpose of this paper is to explore the merits of the idea that dynamical systems theory (also known as chaos theory) provides a model of the mind that can vindicate the language of thought (LOT). I investigate the nature of emergent structure in dynamical systems to assess its compatibility with causally efficacious syntactic structure in the brain. I will argue that anyone who is committed to the idea that the brain's functioning depends on emergent features of dynamical systems should (...) have serious reservations about the LOT. First, dynamical systems theory casts doubt on one of the strongest motives for believing in the LOT: principle P, the doctrine that structure found in an effect must also be found in its cause. Second, chaotic emergence is a double-edged sword. Its tendency to cleave the psychological from the neurological undermines foundations for belief in the existence of causally efficacious representations. Overall, a dynamic conception of the brain sways us away from realist conclusions about the causal powers of representations with constituent structure. (shrink)

I propose a semi-eliminative reduction of Fodors concept of module to the concept of attractor basin which is used in Cognitive Dynamic Systems Theory (DST). I show how attractor basins perform the same explanatory function as modules in several DST based research program. Attractor basins in some organic dynamic systems have even been able to perform cognitive functions which are equivalent to the If/Then/Else loop in the computer language LISP. I suggest directions for future research programs which could find similar (...) equivalencies between organic dynamic systems and other cognitive functions. This type of research could help us discover how (and/or if) it is possible to use Dynamic Systems Theory to more accurately model the cognitive functions that are now being modeled by subroutines in Symbolic AI computer models. If such a reduction of subroutines to basins of attraction is possible, it could free AI from the limitations that prompted Fodor to say that it was impossible to model certain higher level cognitive functions. (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)

Connectionism and classicism, it generally appears, have at least this much in common: both place some notion of internal representation at the heart of a scientific study of mind. In recent years, however, a much more radical view has gained increasing popularity. This view calls into question the commitment to internal representation itself. More strikingly still, this new wave of anti-representationalism is rooted not in armchair theorizing but in practical attempts to model and understand intelligent, adaptive behavior. In this paper (...) we first present, and then critically assess, a variety of recent anti-representationalist treatments. We suggest that so far, at least, the sceptical rhetoric outpaces both evidence and argument. Some probable causes of this premature scepticism are isolated. Nonetheless, the anti-representationalist challenge is shown to be both important and progressive insofar as it forces us to see beyond the bare representational/non-representational dichotomy and to recognize instead a rich continuum of degrees and types of representationality. (shrink)

Given (1) Wittgensteins externalist analysis of the distinction between following a rule and behaving in accordance with a rule, (2) prima facie connections between rule-following and psychological capacities, and (3) pragmatic issues about training, it follows that most, even all, future artificially intelligent computers and robots will not use language, possess concepts, or reason. This argument suggests that AIs traditional aim of building machines with minds, exemplified in current work on cognitive robotics, is in need of substantial revision.

I consider two threats to the idea that on-line intelligent behaviour (the production of fluid and adaptable responses to ongoing sensory input) must or should be explained by appeal to neurally located representations. The first of these threats occurs when extra-neural factors account for the kind of behavioural richness and flexibility normally associated with representation-based control. I show how this anti-representational challenge can be met, if we apply the thought that, to be a representational system, an action-oriented neural system must (...) not only be the source of at least some of the observed behavioural richness and flexibility, it must also feature two architectural traits, namely arbitrariness and homuncularity. Unfortunately, however, this solution opens the door to our second threat to representation. The homuncularity condition will not be met by any system in which the causal contribution of each component is massively context-sensitive and variable over time. I end by discussing the empirical bet that biological nervous systems will not exhibit this style of causation. (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.

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)

It is widely believed that mathematics carries a substantial part of the explanatory burden in science. However, mathematics can also play important heuristic roles of a different kind, being a source of new ideas and approaches, allowing us to build toy models, enhancing expressive power and providing fruitful conceptualizations. In this paper, we focus on the application of dynamical systems theory (DST) within the extended cognition (EC) field of cognitive science, considering this case study to be a good illustration of (...) a general phenomenon. In the paper, we justify both a negative and a positive claim. The negative claim is that dynamical systems theory hardly plays any explanatory role in EC research. We justify our claim by analyzing several accounts of the explanatory role of mathematics and stressing the way mathematical arguments are used in explanations. Our positive claim is that even though, for now, DST has no explanatory power in many of the EC approaches, it still plays an important heuristic role there. In particular, using mathematical notions improves the expressive power of the language and gives a sense of understanding of the phenomena under investigation. The case study of EC allows us to identify and analyze this important role of mathematics, which seems to be neglected in contemporary discussions. (shrink)

The dynamical hypothesis states that cognitive systems are dynamical systems. While dynamical systems play an important role in many cognitive phenomena, the dynamical hypothesis as stated applies to every system and so fails both to specify what makes cognitive systems distinct and to distinguish between proposals regarding the nature of cognitive systems. To avoid this problem, I distinguish several different types of dynamical systems, outlining four dimensions along which dynamical systems can vary: total-state versus partial-state, internal versus external, macroscopic versus (...) microscopic, and systemic versus componential, and illustrate these with examples. I conclude with two illustrations of partial-state, internal, microscopic, componential dynamicism. (shrink)

(Penultimate draft) Embodied Cognition holds that bodily (e.g. sensorimotor) states and processes are directly involved in some higher-level cognitive functions (e.g. reasoning). This challenges traditional views of cognition according to which bodily states and processes are, at most, indirectly involved in higher-level cognition. Although some elements of Embodied Cognition have been integrated into mainstream cognitive science, others still face adamant resistance. In this paper, rather than straightforwardly defend Embodied Cognition against specific objections I will do the following. First, I will (...) present a concise account of embodied conceptual processing and highlight some of its advantages over non-embodied accounts, specifically focusing on the role of metaphors. Second, I will detail the influence of computational metaphors on theories of cognition and evaluation of these theories. Third, I will argue that embodied cognitive mechanisms, specifically those operating through computational metaphors, may drive some of the resistance to Embodied Cognition - and that Embodied Cognition is able to offer a uniquely compelling account of this. Ultimately, this will contribute to an improved understanding of Embodied Cognition, its explanatory power, and how it ought to be evaluated. Additionally, it will shed light on the role of metaphors in shaping philosophical thought and highlight the importance of these influences. (shrink)

Debate on the nature of representation in cognitive systems tends to oscillate between robustly realist views and various anti‐realist options. I defend an alternative view, deflationary realism, which sees cognitive representation as an offshoot of the extended application to cognitive systems of an explanatory model whose primary domain is public representation use. This extended application, justified by a common explanatory target, embodies idealisations, partial mismatches between model and reality. By seeing representation as part of an idealised model, deflationary realism avoids (...) the problems with robust realist views, while keeping allegiance to realism. (shrink)

Despite its centrality in the philosophy of cognitive science, there has been little prior philosophical work engaging with the notion of representation in contemporary NLP practice. This paper attempts to fill that lacuna: drawing on ideas from cognitive science, I introduce a framework for evaluating the representational claims made about components of neural NLP models, proposing three criteria with which to evaluate whether a component of a model represents a property and operationalising these criteria using probing classifiers, a popular analysis (...) technique in NLP (and deep learning more broadly). The project of operationalising a philosophically-informed notion of representation should be of interest to both philosophers of science and NLP practitioners. It affords philosophers a novel testing-ground for claims about the nature of representation, and helps NLPers organise the large literature on probing experiments, suggesting novel avenues for empirical research. (shrink)

Active materials are self-propelled non-living entities which, in some circumstances, exhibit a number of cognitively interesting behaviors such as gradient-following, avoiding obstacles, signaling and group coordination. This has led to scientific and philosophical discussion of whether this may make them useful as minimal models of cognition (Hanczyc, 2014; McGivern, 2019). Batterman and Rice (2014) have argued that what makes a minimal model explanatory is that the model is ultimately in the same universality class as the target system, which underpins why (...) it exhibits the same macrobehavior. We appeal to recent research in basal cognition (Lyon et al., 2021) to establish appropriate target systems and essential features of cognition as a target of modeling. Looking at self-propelled oil droplets, a type of active material, we do not find that organization alone indicates that these systems exhibit the essential features of cognition. We then examine the specific behaviors of oil droplets but also fail to find that these demonstrate the essential features of cognition. Without a universality class, Batterman & Rice’s account of the explanatory power of minimal models simply does not apply to cognition. However, we also want to stress that it is not intended to; cognition is not the same type of behavioral phenomena as those found in physics. We then look to the minimal cognition methodology of Beer (1996, 2020a, b) to show how active materials can be explanatorily valuable regardless of their cognitive status because they engage in specific behaviors that have traditionally been expected to involve internal representational dynamics, revealing misconceptions about the cognitive underpinnings of certain, specific behaviors in target systems where such behaviors are cognitive. Further, Beer’s models can also be genuinely explanatory by providing dynamical explanations. (shrink)

3.2.2. The principle of conceptual containment ........................... 116 3.3.3. The physical human subject or the “I” ............................... 119 3.4. The hyperverse and its EDWs – the antimetaphysical foundation of the EDWs perspective ........................................... 150 Part II. Applications Chapter 4. Applications to some notions from philosophy of mind .. 159 4.1. Levels and reduction vs. emergence ............................................. 160 4.2. Qualia, Kant and the “I” ............................................................... 181 4.3. Mental causation and supervenience ............................................ 190 Chapter 5. Applications to some notions from cognitive science (...) ...... 200 5.1. Computationalism ........................................................................ 200 5.2. Connectionism .............................................................................. 211 5.3. The dynamical system approach .................................................. 223 5.4. Robotics ........................................................................................ 232 5.5. Dichotomies concerning the notion of mental representation and processing .............................................................................. 243 5.6. The EDWs perspective and some key elements in cognitive science .......................................................................................... 249 5.7. The relation between key elements and some philosophical distinctions ................................................................................... 264 5.8. Cognitive neuroscience ................................................................ 267 5.9. The status of any living entity ...................................................... 277 Chapter 6. Applications to some notions from philosophy of science and science ............................................................................ 281 6.1. A glance at logical positivism ...................................................... 285 6.2. Carnap’s linguistic frameworks .................................................... 289 6.3. Carnap vs. Gödel or syntactic vs. semantic .................................. 292 6.4. Carnap vs. Quine or rational reconstruction vs. naturalized epistemology ................................................................................ 295 6.5. Quine’s ontological relativity ....................................................... 296 6.6. Goodman’s relativity .................................................................... 298 6.7. Putnam and the rejection of the “thing-in-itself” .......................... 299 6.8. Friedman’s relative constitutive a priori principles....................... 301 6.9. Some notions from quantum mechanics ....................................... 305 6.10. The status of the external non-living epistemologically different entities ....................................................................................... 343 Conclusion .............................................................................................. 361 References .............................................................................................. 369. (shrink)

Some philosophers search for the mark of the cognitive: a set of individually necessary and jointly sufficient conditions identifying all instances of cognition. They claim that the mark of the cognitive is needed to steer the development of cognitive science on the right path. Here, I argue that, at least at present, it cannot be provided. First (§2), I identify some of the factors motivating the search for a mark of the cognitive, each yielding a desideratum the mark is supposed (...) to satisfy (§2.1). I then (§2.2) highlight a number of tensions in the literature on the mark of the cognitive, suggesting they’re best resolved by distinguishing two distinct programs. The first program (§3) is that of identifying a mark of the cognitive capturing our everyday notion of cognition. I argue that such a program is bound to fail for a number of reasons: it is not clear whether such an everyday notion exists; and even if it existed, it would not be able to spell out individually necessary and jointly sufficient conditions for cognition; and even if it were able to spell them out, these conditions won’t satisfy the desiderata a mark of the cognitive should satisfy. The second program is that of identifying a mark of the cognitive spelling out a genuine scientific kind. But the current state of fragmentation of cognitive science, and the fact that it is splintered in a myriad of different research traditions, prevent us from identifying such a kind. And we have no reason to think that these various research traditions will converge, allowing us to identify a single mark. Or so, at least, I will argue in (§4). I then conclude the paper (§5) deflecting an intuitive objection, and exploring some of the consequences of the thesis I have defended. (shrink)

There has been much criticism of the idea that Friston's free-energy principle can unite the life and mind sciences. Here, we argue that perhaps the greatest problem for the totalizing ambitions of its proponents is a failure to recognize the importance of evolutionary dynamics and to provide a convincing adaptive story relating free-energy minimization to organismal fitness.

Metaphors of mind and their elaboration into models serve a crucial explanatory role in psychology. In this article, an attempt is made to describe how biology and engineering provide the predominant metaphors for contemporary psychology. A contrast between the discursive and descriptive functions of metaphor use in theory construction serves as a platform for deliberation upon the pragmatic consequences of models derived therefrom. The conclusion contains reflections upon the possibility of an integrative interdisciplinary psychology.

In the recent twenty-year retrospective issue of Animal Behavior and Cognition, Povinelli and Henley (2020) argue that a host of comparative studies into “complex cognition” suffer, fatally, from a theoretical confusion. To rectify the problem, they issue the following challenge: alongside specifications of the higher-order capacity to be tested, provide hypotheses of the mechanism(s) necessary to implement it. They spearhead this effort with a discussion of how the Relational Reinterpretation Hypothesis (RRH) provides just such an account. In the first part (...) of the paper, I argue that RRH is neither necessary nor sufficient to explain the second-order behavior in question. In part two, I describe an alternative hypothesis, externalism, that does sufficiently account for it. Further, it opens new avenues of comparative research. (shrink)

The computational metaphor for mind is still the central guiding idea in cognitive science despite many insightful and well-founded rejections of it. There is good reason for its staying power: when we are at our cognitive best, we reason about our world with our concepts. But the challengers are right, I argue, in insisting that no reductive account of that capacity is forthcoming. Here I describe an externalist account that grounds representations in organism-level engagement with its environment, not in its (...) neural activity. (shrink)

4Es approaches to cognition draw an unconventional picture of cognitive processes and of the mind. Instead of conceiving of cognition as a process that always takes place within the boundaries of the skull and the skin, these approaches hold that cognition is a situated process that often extends beyond human agents’ physical boundaries. In particular, supporters of the extended mind theory and of the enactive approach claim that embodied action in a perceptually complex environment is constitutive of cognitive processes, and (...) thus of the mind. (Chapter 1). Although both draw an extended picture of cognition and of the mind, supporters of the extended mind and supporters of the enactive approach disagree on the value of internal representations in perceptually-guided action. The extended mind theory holds that we need to posit internal action-oriented representations (AORs). AORs are valuable -the argument goes- because they account for action-selection, action-control, and for the prediction of incoming perceptual information. Advocates of the enactive approach to cognition, instead, argue against AORs. Firstly, they argue that AORs do not fulfill the necessary conditions for the identification of representational entities. Therefore, that of AOR is an ill-conceived epistemic construct. Secondly, they argue that AORs are expressive of an internalist prejudice, which makes the extended mind theory weaker than it should be from an explanatory and metaphysical point of view. I endorse both these arguments advanced by supporters of the enactive approach. Moreover, through a semiotic analysis of the construct and of the workings of AORs, I show that AORs are not active at all. Hence, I argue that AORs do not do the job they are supposed to do: extending the mind’s boundaries by explaining our perceptual relation with the world as an active, embodied, and world-involving process. Therefore, I suggest that the construct of AOR ought to be dismissed - at least in current projects in 4Es cognition (Chapter 2). I argue that similar arguments apply to recent attempts to make predictive processing accounts of perceptually-guided action more aligned with 4Es approaches to cognitive science by appealing to predictive internal models of our perceptual world. I thus propose an alternative explanation of the key features of perceptually-guided action that AORs and these internal models are supposed to be grasp. Action-control, action-selection, and the anticipatory aspects of action-perception loops can be explained by appealing to embodied actions in a field of relevant affordances, which are perceived as such based on the agent’s motor skills and motives. Furthermore, I suggest that, by combining the enactive approach to cognition with an analysis of the indexical features of our perceptual environment, we can explain perceptually-guided action in a way that truly accounts for our minds as entities that often extend beyond our skulls and skin. And we can do so without holding onto spooking entities like AORs and internal predictive models. (Chapter 3). (shrink)

Biogenic approaches investigate cognition from the standpoint of evolutionary function, asking what cognition does for a living system and then looking for common principles and exhibitions of cognitive strategies in a vast array of living systems—non-neural to neural. One worry which arises for the biogenic approach is that it is overly permissive in terms of what it construes as cognition. In this paper I critically engage with a recent instance of this way of criticising biogenic approaches in order to clarify (...) their theoretical commitments and prospects. In his critique of the biogenic approach, Fred Adams uses the presence of intentional states with conceptual content as a criterion to demarcate cognition-driven behaviour from mere sensory response. In this paper I agree with Adams that intentionality is the mark of the cognitive, but simultaneously reject his overly restrictive conception of intentionality. I argue that understanding intentionality simpliciter as the mark of the mental is compatible with endorsing the biogenic approach. I argue that because cognitive science is not exclusively interested in behaviour driven by intentional states with the kind of content Adams demands, the biogenic approach’s status as an approach to cognition is not called into question. I then go on to propose a novel view of intentionality whereby it is seen to exist along a continuum which increases in the degree of representational complexity: how far into the future representational content can be directed and drive anticipatory behaviour. Understanding intentionality as existing along a continuum allows biogenic approaches and anthropogenic approaches to investigate the same overarching capacity of cognition as expressed in its different forms positioned along the continuum of intentionality. Even if all organisms engage in some behaviour that is driven by weak intentional dynamics, this does not suggest that every behaviour of all organisms is so driven. As such, the worry that the biogenic approach is overly permissive can be avoided. (shrink)

Philosophers of science have recently begun to pay more attention to scientific practice, moving away from the discipline’s focus on theories. The creation of the Society for Philosophy of Science in Practice in 2006, as well as the emergence of scholarship on experimental practice (e.g. Sullivan 2009; 2010; 2016) as well as on the tools scientists use to construct explanations and theories (e.g. Feest 2011) all point to a disciplinary shift towards a more practice-conscious philosophy of science. In addition, scholars (...) are realizing the potential social relevance of philosophy of science and identifying the obstacles that stand in the way of realizing said potential (e.g. Douglas 2010). The aim of this dissertation is to propose a novel descriptive framework for philosophy of science, one that rests on the idea that scientific practice should be described as accurately as possible so that philosophical discussions of science rest on a solid descriptive base and can more easily be of use in engaging users and practitioners of science. The dissertation is organized along the stages of developing what I call the dynamic-iterative model of scientific practice. In chapter 1, I clarify the project’s philosophical background and outline six conditions of adequacy on a descriptive model of science. These conditions allow me to evaluate the three descriptive models reviewed in chapter 2. Chapter 3 combines Nickles’ problem-solving view of science (1981) with core insights from the heuristics and biases literature into a workable version of the dynamic-iterative model. I then apply the model to the case of place cell research in chapter 4 as a test of the model’s usefulness and applicability. In chapter 5 I evaluate the model with respect to my six conditions and assess its strengths and weaknesses. The dynamic-iterative model is a flexible descriptive framework that not only allows for more complete philosophical analyses of cases than other current models, but also supports important practical applications. (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.

The paper draws on scientific resources formed around the notion of Free Energy Principle to reconstruct two well-known defences of panpsychism. I reconstruct the argument from continuity by expanding the mind-life continuity thesis under the rubric of the Free Energy Principle (FEP), by showing that FEP does not provide an objective criterion for demarcating the living from the inanimate. Then I will reconstruct the argument from intrinsic nature. The FEP-based account of consciousness is centred on the notion of ‘temporal depth’ (...) of generative models. I argue that even evolution can be modelled as a temporally deep system. Since we have no access to the intrinsic perspective of evolution to see whether or not it models itself as a temporally deep system, we must draw an analogy from our own case and conclude that evolution is consciousness involving. Thus the paper reconstructs two main arguments for panpsychism. (shrink)

In this paper I look into a problem concerning the characterization of the main conceptual commitments of the ‘post-cognitivist’ theoretical framework. I first consider critically a proposal put forward by Rowlands (2010), which identifies the theoretical nucleus of post-cognitivism with a convergence of the theses of the extended and the embodied mind. The shortcomings I find in this proposal lead me to an indepedent and wider issue concerning the apparent tensions between functionalism and the embodied and enactive approaches.

This thesis contributes to a better conceptual understanding of how self-organized control works. I begin by analyzing the control problem and its solution space. I argue that the two prominent solutions offered by classical cognitive science (centralized control with rich commands, e.g., the Fodorian central systems) and embodied cognitive science (distributed control with simple commands, such as the subsumption architecture by Rodney Brooks) are merely two positions in a two-dimensional solution space. I outline two alternative positions: one is distributed control (...) with rich commands, defended by proponents of massive modularity hypothesis; the other is centralized control with simple commands. My goal is to develop a hybrid account that combines aspects of the second alternative position and that of the embodied cognitive science (i.e., centralized and distributed controls with simple commands). Before developing my account, I discuss the virtues and challenges of the first three. This discussion results in a set of criteria for successful neural control mechanisms. Then, I develop my account through analyzing neuroscientific models of decision-making and control with the theoretical lenses provided by formal decision and social choice theories. I contend that neural processes can be productively modeled as a collective of agents, and neural self-organization is analogous to democratic self-governance. In particular, I show that the basal ganglia, a set of subcortical structures, contribute to the production of coherent and intelligent behaviors through implementing “democratic" procedures. Unlike the Fodorian central system—which is a micro-managing “neural commander-in-chief”—the basal ganglia are a “central election commission.” They delegate control of habitual behaviors to other distributed control mechanisms. Yet, when novel problems arise, they engage and determine the result on the basis of simple information (the votes) from across the system with the principles of neurodemocracy, and control with simple commands of inhibition and disinhibition. By actively managing and taking advantage of the wisdom-of-the-crowd effect, these democratic processes enhance the intelligence and coherence of the mind’s final "collective" decisions. I end by defending this account from both philosophical and empirical criticisms and showing that it meets the criteria for successful solution. (shrink)

Over the last 30 years, representationalist and dynamicist positions in the philosophy of cognitive science have argued over whether neurocognitive processes should be viewed as representational or not. Major scientific and technological developments over the years have furnished both parties with ever more sophisticated conceptual weaponry. In recent years, an enactive generalization of predictive processing – known as active inference – has been proposed as a unifying theory of brain functions. Since then, active inference has fueled both representationalist and dynamicist (...) campaigns. However, we believe that when diving into the formal details of active inference, one should be able to find a solution to the war; if not a peace treaty, surely an armistice of a sort. Based on an analysis of these formal details, this paper shows how both representationalist and dynamicist sensibilities can peacefully coexist within the new territory of active inference. (shrink)

It is widely thought that philosophical behaviorism is an untenable and outdated theory of mind. It is generally agreed, in particular, that the view generates a vicious circularity problem. There is a standard solution to this problem for functionalism, which utilizes the formulation of Ramsey sentences. I will show that this solution is also available for behaviorism if we allow quantification over the causal bases of behavioral dispositions. Then I will suggest that behaviorism differs from functionalism mainly in its commitment (...) to anti-representationalism, and I will offer two new objections to anti-representationalism. The first will be based on considerations concerning the contents of desires and intentions. The second objection concerns inner speech and mental imagery. We will see that the objections are of relevance to contemporary debates, as they apply with equal force to the currently popular anti-representationalist versions of embodied and enactive cognition. (shrink)

The debate over the explanatory nature of cognitive models has been waged mostly between two factions: the mechanists and the dynamical systems theorists. The former hold that cognitive models are explanatory only if they satisfy a set of mapping criteria, particularly the 3M/3m* requirement. The latter have argued, pace the mechanists, that some cognitive models are both dynamical and constitute covering-law explanations. In this paper, I provide a minimal model interpretation of dynamical cognitive models, arguing that this both provides needed (...) clarity to the mechanist versus dynamicist divide in cognitive science and also paves the way towards further insights about scientific explanation generally. (shrink)

Dynamical systems play a central role in explanations in cognitive neuroscience. The grounds for these explanations are hotly debated and generally fall under two approaches: non-mechanistic and mechanistic. In this paper, I first outline a neurodynamical explanatory schema that highlights the role of dynamical systems in cognitive phenomena. I next explore the mechanistic status of such neurodynamical explanations. I argue that these explanations satisfy only some of the constraints on mechanistic explanation and should be considered pseudomechanistic explanations. I defend this (...) argument against three alternative interpretations of the neurodynamical explanatory schema. The independent interpretation holds that neurodynamical explanations and mechanisms are independent. The constitutive interpretation holds that neurodynamical explanations are constitutive but otherwise non-mechanistic. Both the independent and constitutive interpretations fail to account for all the features of neurodynamical explanations. The partial interpretation assumes that the targets of dynamical systems models are mechanisms and so holds that neurodynamical explanations are incomplete because they lack mechanistic details. I contend instead that the targets of those models are dynamical systems distinct from mechanisms and defend this claim against several objections. I conclude with a defense of the pseudomechanistic interpretation and a discussion of the source of their explanatory power in relation to a causal-mechanical description of the world. (shrink)

Objections to the computational theory of cognition, inspired by twentieth century phenomenology, have tended to fixate on the embodiment and embeddedness of intelligence. In this paper I reconstruct a line of argument that focusses primarily on the abstract nature of scientific models, of which computational models of the brain are one sort. I observe that the critique of scientific abstraction was rather commonplace in the philosophy of the 1920s and 30s and that attention to it aids the reading of The (...) Organism ([1934] 1939) by the neurologist Kurt Goldstein. With this background in place, we see that some brief but spirited criticisms of cybernetics by two later thinkers much influenced by Goldstein, Georges Canguilhem (1963) and Maurice Merleau-Ponty (1961), show continuity with the earlier discussions of abstraction in science. (shrink)

Ecological psychologists and enactivists agree that the best explanation for a large share of cognition is nonrepresentational in kind. In both ecological psychology and enactivist philosophy, then, the task is to offer an explanans that does not rely on representations. Different theorists within these camps have contrasting notions of what the best kind of nonrepresentational explanation will look like, yet they agree on one central point: instead of focusing solely on factors interior to an agent, an important aspect of cognition (...) is found in the link or coupling between an agent and the external world. This link is fluid, dynamic, and active in a variety of ways, and we do not need to add any internal extra something in the perception-action-cognition process. At the same time, even devout defenders of ecological psychology and enactivism recognize that plenty happens inside an agent during cognition. In particular, no one denies that the brain plays an important role. What, then, is the role of the brain if it’s not in the game of representing the environment? One possible option is to describe the brain as a resonant organ instead of a representational organ. In this paper we consider the history of resonance in more detail. Particular focus will be placed on two different sets of approaches that have developed the concept of resonance: a representational reading of resonance and a nonrepresentational, dynamic account of resonance. We then apply these accounts to a case study on music performance, specifically in the context of standard tonal jazz. From this application, we propose that a nonrepresentational resonance account consistent with both enactivism and ecological psychology is a viable way of explaining jazz performance. We conclude with future considerations on research regarding the brain as a resonant organ. (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)

Many researchers have argued that humanity will create artificial general intelligence (AGI) within the next twenty to one hundred years. It has been suggested that AGI may inflict serious damage to human well-being on a global scale ('catastrophic risk'). After summarizing the arguments for why AGI may pose such a risk, we review the fieldʼs proposed responses to AGI risk. We consider societal proposals, proposals for external constraints on AGI behaviors and proposals for creating AGIs that are safe due to (...) their internal design. (shrink)