Structural representations are increasingly popular in philosophy of cognitive science. A key virtue they seemingly boast is that of meeting Ramsey's job description challenge. For this reason, structural representations appear tailored to play a clear representational role within cognitive architectures. Here, however, I claim that structural representations do not meet the job description challenge. This is because even our most demanding account of their functional profile is satisfied by at least some receptors, which paradigmatically fail the job (...) description challenge. Hence, the functional profile typically associated with structural representations does not identify representational posits. After a brief introduction, I present, in the second section of the paper, the job description challenge. I clarify why receptors fail to meet it and highlight why, as a result, they should not be considered representations. In the third section I introduce what I take to be the most demanding account of structural representations at our disposal, namely Gładziejewski's account. Provided the necessary background, I turn from exposition to criticism. In the first half of the fourth section, I equate the functional profile of structural representations and receptors. To do so, I show that some receptors boast, as a matter of fact, all the functional features associated with structural representations. Since receptors function merely as causal mediators, I conclude structural representations are mere causal mediators too. In the second half of the fourth section I make this conclusion intuitive with a toy example. I then conclude the paper, anticipating some objections my argument invites. (shrink)

Cognition can often be modeled as the transformation of a set of variables into another. At least two kinds of entities are needed in this process: signals and coders. Representations are usually taken to be signals, but sometimes they are the coders: sometimes the computational complexity of variable transformations can be strikingly reduced by relying on a structure that mirrors that of some task-relevant entity. These kinds of coders are what philosophers call structural representations.

It is argued that a number of important, and seemingly disparate, types of representation are species of a single relation, here called structural representation, that can be described in detail and studied in a way that is of considerable philosophical interest. A structural representation depends on the existence of a common structure between a representation and that which it represents, and it is important because it allows us to reason directly about the representation (...) in order to draw conclusions about the phenomenon that it depicts. The present goal is to give a general and precise account of structural representation, then to use that account to illuminate several problems of current philosophical interest — including some that do not initially seem to involve representation at all. In particular, it is argued that ontological reductions (like that of the natural numbers to sets), compositional accounts of semantics, several important sorts of mental representation, and (perhaps) possible worlds semantics for intensional logics are all species of structural representation and are fruitfully studied in the framework developed here. (shrink)

The aim of this chapter is to provide a primer on structured mental representations and their place in philosophical and scientific theorizing. We discuss four questions: 1. What does it mean to say that a psychological representation is structured? 2. Why does a representation’s structure matter? 3. What are examples of possible representational structures? 4. How can such representational structures be discovered empirically? -/- We encourage several pluralist perspectives concerning structured mental representation. The first is pluralism about (...) which mental capacities make use of structured representations. Structured representations are not exclusive to evolutionarily and cognitively advanced faculties of language, thought, and reasoning; they underwrite a wide variety of mental capacities. The second perspective is pluralism about the neural underpinnings of representational structures. There are many ways a structured representation might be realized in populations of cells. The third perspective concerns pluralism about types of representational structure. Structured representations are not restricted to sentences and formulas; they can take a wide variety of forms. (shrink)

The brain is an operationally closed system. At it’s boundary, every incoming signal gets translated into neural activity. The intrinsic nature of the distal causes perturbing the brain at its sensory surfaces cannot be grasped from the inside. Moreover, the brain exploits change detection and relational coding. Hence, the external relations between any distal causes are transformed into internal relations between neural activities. The picture of a thoroughgoing structuralism about the mind emerges: all mental states are relationally individuated and thereby (...) provide structural representations. But structuralism is vulnerable to a rather generic logico-mathematical problem: the Newman problem. The specific “Newman problem of the brain” is the concern that the brain’s operational closure is accompanied by a representational closure, where neither the intrinsic nature of the distal causes nor the nature of the external relations can be grasped from the inside. Potentially, this applies to any operationally closed structural representation system, including brains and AI systems. If the Newman problem persists, then such systems “know” nothing, the outside world remains completely hidden. This is nothing less than a skeptical scenario of the most extreme form. However, I will present a solution to this conundrum. It works by “spatio-temporal grounding”: spatial and temporal relations are unalteredly transferred from the external world to systems of structural representation. (shrink)

Recent years have seen an increasing amount of attention devoted to the subject of structural representation. Is there one type of structural representation or many? How do they differ from other types of representation? Are they really a genuine type of representation in the first place? All good questions, which I will address indirectly by arguing that structural representations are nothing more than analog representations. Understanding them as such provides some much needed theoretical (...) clarity about this type of representation. Typical analog representations (e.g., liquid thermometers or analog clocks) are often "one-dimensional;" the corresponding one-dimensional characterization of these representations can be extended into multiple dimensions, which elucidates the structure of more complex analog representations, such as photographs, maps, or three-dimensional models. However, this analysis applies to structural representations without remainder. The upshot is that we can directly apply what we have learned about analog representation to our understanding of structural representation, which, if not directly answering these recent questions, greatly adds to our theoretical resources for doing so. The analog wheel has already been invented; we need not reinvent it for structural representation. (shrink)

A promising strategy for defending the role that representation plays in explanations of cognition frames the concept in terms of internal models or map‐like mechanisms. “Structural representation” offers an account of representation that is grounded in well‐specified, empirical criteria. However, anti‐representationalists continue to press the issue of how to account for the paradigmatic semantic properties of representation at the subpersonal level. In this paper, I offer an account of how the proponent of structural (...) class='Hi'>representation should think about content. There are really two problems of content any account of representation must overcome: the “hard problem of content” and the “content determination problem.” I argue that the structural representation account has the resources to provide a naturalistically respectable notion of content that overcomes both problems. (shrink)

This paper centers around the notion that internal, mental representations are grounded in structural similarity, i.e., that they are so-called S-representations. We show how S-representations may be causally relevant and argue that they are distinct from mere detectors. First, using the neomechanist theory of explanation and the interventionist account of causal relevance, we provide a precise interpretation of the claim that in S-representations, structural similarity serves as a “fuel of success”, i.e., a relation that is exploitable for the (...) representation using system. Then, we discuss crucial differences between S-representations and indicators or detectors, showing that—contrary to claims made in the literature—there is an important theoretical distinction to be drawn between the two. (shrink)

In Representation Reconsidered , William Ramsey suggests that the notion of structural representation is posited by classical theories of cognition, but not by the ‘newer accounts’ (e.g. connectionist modeling). I challenge the assertion about the newer accounts. I argue that the newer accounts also posit structural representations; in fact, the notion plays a key theoretical role in the current computational approaches in cognitive neuroscience. The argument rests on a close examination of computational work on the oculomotor (...) system. (shrink)

Philosophers interested in the theoretical consequences of predictive processing often assume that predictive processing is an inferentialist and representationalist theory of cognition. More specifically, they assume that predictive processing revolves around approximated Bayesian inferences drawn by inverting a generative model. Generative models, in turn, are said to be structural representations: representational vehicles that represent their targets by being structurally similar to them. Here, I challenge this assumption, claiming that, at present, it lacks an adequate justification. I examine the only (...) argument offered to establish that generative models are structural representations, and argue that it does not substantiate the desired conclusion. Having so done, I consider a number of alternative arguments aimed at showing that the relevant structural similarity obtains, and argue that all these arguments are unconvincing for a variety of reasons. I then conclude the paper by briefly highlighting three themes that might be relevant for further investigation on the matter. (shrink)

An approach to argument macrostructure -- The dialectical nature of argument -- Toulmin's problematic notion of warrant -- The linked-convergent distinction, a first approximation -- Argument structure and disciplinary perspective : the linked-convergent versus multiple-co-ordinatively compound distinctions -- The linked-convergent distinction, refining the criterion -- Argument structure and enthymemes -- From analysis to evaluation.

Structural representations are likely the most talked about representational posits in the contemporary debate over cognitive representations. Indeed, the debate surrounding them is so vast virtually every claim about them has been made. Some, for instance, claimed structural representations are different from indicators. Others argued they are the same. Some claimed structural representations mesh perfectly with mechanistic explanations, others argued they can’t in principle mash. Some claimed structural representations are central to predictive processing accounts of cognition, (...) others rebuked predictive processing networks are blissfully structural representation free. And so forth. Here, I suggest this confusing state of affairs is due to the fact that the term “structural representations” is applied to a number of distinct conceptions of representations. In this paper, I distinguish four such conceptions, argue that these four conceptions are actually distinct, and then show that such a fourfold distinction can be used to clarify some of the most pressing questions concerning structural representations and their role in cognitive theorizing, making these questions more easily answerable. (shrink)

This chapter introduces a structural account of representation through partial structures and examines its ontological commitments. It is pointed out that structural approaches to scientific representation emphasize the crucial role played by structures in representing salient features of the world. It is common to present and, in some cases, even to reify such structures as abstract entities, in particular as set-theoretic constructs. Against this view, it is argued that no such reification is called for and that (...) several strategies can be articulated to avoid commitment to set-theoretic structures in the defense of structural representation. In the end, one can favor the latter without being platonist about the former. (shrink)

Leech et al.'s model proposes representing relations as primed transformations rather than as structured representations (explicit representations of relations and their roles dynamically bound to fillers). However, this renders the model unable to explain several developmental trends (including relational integration and all changes not attributable to growth in relational knowledge). We suggest looking to an alternative computational model that learns structured representations from examples.

The goal of this paper is to show that the information carried by a structural representation can be decomposed into the information carried by its component parts. In particular, the relations between the components of a structural representation carry quantifiable information about the relations between components of their signifieds. It follows that the information carried by cognitive structural representations, including cognitive maps, can in principle be quantified and decomposed. This is perhaps surprising given that the (...) formal tools of communication theory have typically only been applied to simpler representation-like states without significant structure, such as detectors or indicators. In the final section I consider using computational complexity theory to capture the processing advantages afforded by structural representation. (shrink)

The perceptual symbol system view assumes that perceptual representations have a role-argument structure. A role-argument structure is often incorporated into amodal symbol systems in order to explain conceptual functions like abstraction and rule use. The power of perceptual symbol systems to support conceptual functions is likewise rooted in its use of structure. On Barsalou's account, this capacity to use structure (in the form of frames) must be innate.

The Protein Ontology (PRO) provides a formal, logically-based classification of specific protein classes including structured representations of protein isoforms, variants and modified forms. Initially focused on proteins found in human, mouse and Escherichia coli, PRO now includes representations of protein complexes. The PRO Consortium works in concert with the developers of other biomedical ontologies and protein knowledge bases to provide the ability to formally organize and integrate representations of precise protein forms so as to enhance accessibility to results of protein (...) research. PRO (http://pir.georgetown.edu/pro) is part of the Open Biomedical Ontologies (OBO) Foundry. (shrink)

An interesting feature of some sets of representations is that their structure mirrors the structure of the items they represent. Founding an account of representational content on isomorphism, homomorphism or structural resemblance has proven elusive, however, largely because these relations are too liberal when the candidate structure over representational vehicles is unconstrained. Furthermore, in many cases where there is a clear isomorphism, it is not relied on in the way the representations are used. That points to a potential resolution: (...) that an isomorphism must be used, hence usable, if it is to be an ingredient in a theory of content. This paper argues that the class of exploitable isomorphisms can indeed play a content-constituting role. (shrink)

My aim in this paper is to investigate what epistemic role, if any, do appeals to representations play in cognitive neuroscience. I suggest that while at present they seem to play something in between a minimal and a substantive explanatory role, there is reason to believe that representations have a substantial contribution to the construction of neuroscientic explanations of cognitive phenomena.

Availability of the notion that the brain or mind represents the world by instantiating structures similar to relations amongst external items is crucial to the idea than an AI could represent the world in the same way that a human being does. This paper looks at the historical emergence of this notion within the structuralist movement in science, mathematics and philosophy seen in the late nineteenth and early twentieth century. Cassirer’s philosophy is a crystallisation of some these tendencies, and Heidegger’s (...) disagreement with Cassirer over the role of sensory intuition in Kant’s epistemology forms the basis for a Heideggerian critique of AI different from the generalised anti-representationalism of Dreyfus and other proponents of embodied cognition. (shrink)

We challenge Bruineberg et al's view that Markov blankets are illicitly reified when used to describe organismic boundaries. We do this both on general methodological grounds, where we appeal to a form of structural realism derived from Bayesian cognitive science to dissolve the problem, and by rebutting specific arguments in the target article.

Some philosophers have offered structural representations as an alternative to indicator-based representations. Motivating these philosophers is the belief that an indication-based analysis of representation exhibits two fatal inadequacies from which structural representations are spared: such an analysis cannot account for the causal role of representational content and cannot explain how representational content can be made determinate. In fact, we argue, indicator and structural representations are on a par with respect to these two problems. This should not (...) be surprising, we contend, given that the distinction between indicator and structural representations is better conceived as one involving degree rather than kind. (shrink)

Predictive processing posits that prediction-error minimization underlies all perception, action, and cognition. Yet, despite its considerable popularity and explanatory scope, it is unclear how this enables higher-level cognitive abilities, such as representing and reasoning over abstract concepts. We combine insights from predictive processing, structural representations and grounded cognition to address this issue. It has been argued from predictive processing and the free energy principle that an anticipatory model of the person-relevant environment is simulated. Structural representations state that these (...) representations are isomorphic to, i.e., retain the relational pattern of the world. Building on this assembly, grounded cognition research provides three insights into how abstract concepts are represented. First, a hierarchical organization allows abstracting from specific sensory qualities. Second, language glues together sensory qualities into representations that share no intrinsic properties, and acts as a social tool. Third, metaphoric mapping allows fragments of concrete percepts to represent abstract concepts. By transplanting these three insights to predictive processing’s (structural) hierarchical generative model, we explain higher-level cognition through detached models of perception and action simulations, isomorphic to actual behavior. This constitutes a significant expansion to life-mind continuity approaches by providing specific mechanisms for how the principles driving the emergence of life also account for sophisticated higher-level cognition in humans. By synthesizing insights from these literatures, we generate a coherent description of higher-level cognition under predictive processing. (shrink)

Peter Godfrey-Smith recently introduced the idea of representational ‘organization’. When a collection of representations form an organized family, similar representational vehicles carry similar contents. For example, where neural firing rate represents numerosity (an analogue magnitude representation), similar firing rates represent similar numbers of items. Organization has been elided with structural representation, but the two are in fact distinct. An under-appreciated merit of representational organization is the way it facilitates computational processing. Representations from different organized families can interact, (...) for example to perform addition. Their being organized allows them to implement a useful computation. Many of the cases where organization has seemed significant, but which fall short of structural representation, are cases where representational organization underpins a computationally useful processing structure. (shrink)

Structural Omission, originated by Deborah Scott, is a framework in contemporary realist painting that addresses the limits of observation, perception, and knowing. It is not an abstract theory but a practice formalized through three principles—Ground (Perceptual Limits), Structure (Structural Incompleteness), and Consequence (Narrative Without Resolution). It organizes painting around what can be seen and what remains beyond reach, holding the known and the unknowable together. This paper defines Structural Omission as an epistemological framework that repositions realism after (...) the collapse of certainty. By connecting art practice to the philosophical problem of incomplete knowledge, it proposes that absence within representation can operate as load-bearing structure rather than deficiency. Drawing on thinkers such as Michael Fried, Jacques Rancière, Roland Barthes, Maurice Merleau-Ponty, and Ludwig Wittgenstein, the text argues that Structural Omission offers realism a conceptual survival strategy in an era of algorithmic completion and digital closure. (shrink)

This paper develops a theory of analog representation. We first argue that the mark of the analog is to be found in the nature of a representational system’s interpretation function, rather than in its vehicles or contents alone. We then develop the rulebound structure theory of analog representation, according to which analog systems are those that use interpretive rules to map syntactic structural features onto semantic structural features. The theory involves three degree-theoretic measures that capture three (...) independent ways in which a system can be more or less analog. We explain how our theory improves upon prior accounts of analog representation, provides plausible diagnoses for novel challenge cases, extends to hybrid systems that are partially analog and partially symbolic, and accounts for some of the advantages and disadvantages of representing analogically versus symbolically. (shrink)

Basic large language models (LLMs) have no direct contact with extra-linguistic reality: Their inputs, outputs and training data consist solely of text. Can they represent the world beyond that text, nevertheless? This paper considers whether LLMs represent real-world domains partly thanks to structural correspondences between their internal states and those domains. I clarify the requirements for a structural correspondence to play a genuinely content-grounding role, and argue (i) that it is a live empirical possibility that text-based LLMs meet (...) those requirements with respect to real-world contents, but (ii) that this requires carefully eliminating alternative, more deflationary, content assignments. (shrink)

Five experiments investigated the role of spatial connectedness between a pair of objects presented in the change detection task for the actual capacity of visual working memory (VWM) in healthy young adults (total N = 405). Three experiments yielded a surprising nonlinear relationship between the proportion of pair-wise connected objects and capacity, with the highest capacity observed for homogenous displays, when either all objects were connected or disjointed. A drop in capacity, ranging from an average of a quarter of an (...) object out of three objects maintained in VWM, was noted when only some objects were connected while others were disjointed. As indicated by another two experiments, this effect was specific to double-feature encoding, but disappeared when single visual features had to be memorized. No existing theoretical model of VWM can directly explain this novel effect. Overall, the nonlinear effect of spatial connectedness implies that representations in VWM possess hierarchical structure defined by wholes, parts, features, and their relations, and the heterogeneity of such a structure hinders VWM performance, while homogeneity facilitates it. (shrink)

We continue the work of Blok and Jónsson by developing the theory of structural closure operators and introducing the notion of a representation between them. Similarities and equivalences of Blok-Jónsson turn out to be bijective representations and bijective structural representations, respectively. We obtain a characterization for representations induced by a transformer. In order to obtain a similar characterization for structural representations we introduce the notions of a graduation and a graded variable of an M-set. We show (...) that several deductive systems, Gentzen systems among them, are graded M-sets having graded variables, and describe the graded variables in each case. In the last section we show that, for a sentential logic, having an algebraic semantics is equivalent to being representable in an equational consequence. This motivates the extension of the notion of having an algebraic semantics for Gentzen systems, hypersequents systems, etc. We prove that if a closure operator is representable by a transformer, then every extension of it is also representable by the same transformer. As a consequence we obtain that if one of these systems has an algebraic semantics, then so does any of its extensions with the same defining equations. (shrink)

Steven French articulates and defends the bold claim that there are no objects in the world. He draws on metaphysics and philosophy of science to argue for structural realism--the position that we live in a world of structures--and defends a form of eliminativism about objects that sets laws and symmetry principles at the heart of ontology.

Figure 1: A pr ototyp ical exa mple of a three-layer feed forward network, used by Plunkett and M archm an (1 991 ) to simulate learning the past-tense of En glish verbs. The inpu t units encode representations of the three phonemes of the present tense of the artificial words used in this simulation. Th e netwo rk is trained to produce a representation of the phonemes employed in the past tense form and the suffix (/d/, /ed/, or (...) /t/) used on regular verbs. To run the network, each input unit is assigned an activation value o f 0 or 1 , dep ending on whethe r the featu re is present or not. Eac h input unit is conne cted to each of the 30 hidden units by a we ighted conn ection and p rovid es an inp ut to each hidden unit equal to the product of the input unit's activation and the weight. Each hidd en unit's activation is then determined by summing ov er the va lues co ming fro m each inp ut unit to deter mine a netinput, and then applying a non-linear function (e.g., the logistic function 1/(1+e^netinput). Th is whole proced ure is. (shrink)

This paper is concerned with representational explanations of how one experiences and acts with one’s body as an integrated whole. On the standard view, accounts of bodily experience and action must posit a corresponding representational structure: a representation of the body as an integrated whole. The aim of this paper is to show why we should instead favour the minimal view: given the nature of the body, and representation of its parts, accounts of the structure of bodily experience (...) and action need not appeal to a representation of the body as an integrated whole. The argument proceeds by distinguishing two kinds of explanatory roles for representations: standing-in for absent targets and structuring ambiguous sensory information concerning a target. Representations of body-parts are suited to fulfil both kinds of explanatory role, whereas a representation of the body as an integrated whole is only suited to fulfil the latter, as a means of coordinating representations of body-parts. It is then argued that the structure of the body can itself serve as a means of coordinating body-part representations, rendering representation of the body as an integrated whole explanatorily superfluous. (shrink)

An early, very preliminary edition of this book was circulated in 1962 under the title Set-theoretical Structures in Science. There are many reasons for maintaining that such structures play a role in the philosophy of science. Perhaps the best is that they provide the right setting for investigating problems of representation and invariance in any systematic part of science, past or present. Examples are easy to cite. Sophisticated analysis of the nature of representation in perception is to be (...) found already in Plato and Aristotle. One of the great intellectual triumphs of the nineteenth century was the mechanical explanation of such familiar concepts as temperature and pressure by their representation in terms of the motion of particles. A more disturbing change of viewpoint was the realization at the beginning of the twentieth century that the separate invariant properties of space and time must be replaced by the space-time invariants of Einstein's special relativity. Another example, the focus of the longest chapter in this book, is controversy extending over several centuries on the proper representation of probability. The six major positions on this question are critically examined. Topics covered in other chapters include an unusually detailed treatment of theoretical and experimental work on visual space, the two senses of invariance represented by weak and strong reversibility of causal processes, and the representation of hidden variables in quantum mechanics. The final chapter concentrates on different kinds of representations of language, concluding with some empirical results on brain-wave representations of words and sentences. (shrink)

An adequate theory of representation should distinguish between the structure of a representation and the structure of what it represents. I argue that the simplest sorts of transformers (the architecture that underlies most familiar Large Language Models) have only a very lightweight structure for their representations: insofar as they work with the structure of language, they represent it but do not use it. In addition to being interesting in its own right, this also shows how we may use (...) high-level invariants at the computational level to place constraints on representational formats at the algorithmic level. (shrink)

I reply to criticisms from King and Soames and critically examine two aspects of current orthodoxy about propositions: that they are representational and that they are structured. I argue that (especially once one gives up on intrinsically representational propositions) there is no good reason to think that propositions have representational properties, and distinguish a few different senses in which propositions might be structured, expressing some skepticism about the more ambitious ones.

Recent debates over the nature of causation, casual inference, and the uses of causal models in counterfactual analysis, involving inter alia Nancy Cartwright (Hunting Causes and Using Them), James Woodward (Making Things Happen), and Judea Pearl (Causation), hinge on how causality is represented in models. Economists’ indigenous approach to causal representation goes back to the work of Herbert Simon with the Cowles Commission in the early 1950s. The paper explicates a scheme for the representation of causal structure, inspired (...) by Simon, and shows how this representation sheds light on some important debates in the philosophy of causation. This structural account is compared to Woodward’s manipulability account. It is used to evaluate the recent debates – particularly, with respect to the nature of causal structure, the identity of causes, causal independence, and modularity. Special attention is given to modeling issues that arise in empirical economics. (shrink)

The aim of this paper is to show that a comprehensive account of the role of representations in science should reconsider some neglected theses of the classical philosophy of science proposed in the first decades of the twentieth century. More precisely, it is argued that the representational accounts of Helmholtz and Hertz, in which the concept of structure-preservation plays an essential role, still deserve attention for contemporary debates. Following Reichenbach, structure-preserving representations provide a useful device for formulating an up-to-date version (...) of a (relativized) Kantian a priori. An essential feature of modern scientific representations is their mathematical character. That is, representations can be conceived as (partially) structure-preserving maps or functions. This observation suggests an interesting but neglected perspective on the history and philosophy of this concept, namely, that structure-preserving representations are closely related to a priori elements of scientific knowledge. Reichenbach’s early theory of a relativized constitutive but non-apodictic a priori component of scientific knowledge provides a further elaboration of Kantian aspects of scientific representation. To cope with the dynamic aspects of the evolution of scientific knowledge, Cassirer proposed a re-interpretation of the concept of representation that conceived of a particular representation as only one phase in a continuous process determined by pragmatic considerations. Pragmatic aspects of representations are further elaborated in the classical account of C.I. Lewis and the more modern of Hasok Chang who characterized in certain relativized representational a priori assumptions as pragmatically justified metaphysical arguments. (shrink)

In this book, the author develops a new form of structural realism and deals with the problem of representation. The work combines two distinguished developments of the Semantic View of Theories, namely Structural Realism, a flourishing theory from contemporary philosophy of science, and Ronald Giere and colleagues’ Cognitive Models of Science approach. Readers will see how replacing the model-theoretic structures that are at issue in SR with connectionist networks and activations patterns helps us to deal with the (...) problem of representation. The author suggests that cognitive structures are not only the precise formal tools for regimenting the structure of scientific theories but also the tools that the biological brain uses to capture the essential features of its environment. Therefore, replacing model-theoretic structures with cognitive structures allows us to account for the theories-reality relationship on the basis of the most reliable theories of neurology. This is how a new form of SR, called Cognitive Structural Realism is introduced through this book, which articulates and defends CSR, and shows how two diverging branches of SVT can be reconciled. This ground-breaking work will particularly appeal to people who work in the philosophy of science, philosophy of mind and cognitive sciences. (shrink)