Humans are often extraordinary at performing practical reasoning. There are cases where the human computer, slow as it is, is faster than any artificial intelligence system. Are we faster because of the way we perceive knowledge as opposed to the way we represent it? -/- The authors address this question by presenting neural network models that integrate the two most fundamental phenomena of cognition: our ability to learn from experience, and our ability to reason from what has been learned. (...) This book is the first to offer a self-contained presentation of neural network models for a number of computer science logics, including modal, temporal, and epistemic logics. By using a graphical presentation, it explains neural networks through a sound neural-symbolic integration methodology, and it focuses on the benefits of integrating effective robust learning with expressive reasoning capabilities. -/- The book will be invaluable reading for academic researchers, graduate students, and senior undergraduates in computer science, artificial intelligence, machine learning, cognitive science and engineering. It will also be of interest to computational logicians, and professional specialists on applications of cognitive, hybrid and artificial intelligence systems. (shrink)

This article considers an apparent tension between, on the one hand, a widespread belief among literature teachers that the appreciation of a poem involves an experience of form-content inseparability and, on the other hand, these same teachers’ use of paraphrase to encourage appreciation. Using Terrence Deacon’s model of art experience, I argue that the tensions of this ‘paraphrase paradox’ mirror tensions inherent in poetic experience. Section II draws upon work by Rafe McGregor, Peter Lamarque, and Peter Kivy to frame an (...) approach to the form-content distinction, and to offer a brief overview of the paraphrase paradox. Sections III-IV summarize Deacon’s model of aesthetic experience, and argue that this model implies that poetic experience both triggers an impulse towards paraphrase, and frustrates this impulse. Section V looks at implications for the poetry teacher’s attempts to navigate the paraphrase paradox. Section VI tests these implications through an analysis of Philip Larkin’s poem ‘Faith Healing’. (shrink)

This book explores why, regarding practical reasoning, humans are sometimes still faster than artificial intelligence systems. It is the first to offer a self-contained presentation of neural network models for many computer science logics.

Consciousness6 carries the connotation of a state of consciousness . It is an emergent property of a gestalt phenomenon, namely the psychophysiological state of the organism . In this article, I extend my previous discussion of states of consciousness , embedding this within the wider perspective of both Gestalt psychology and psychoanalytic ego psychology. Gestalt notions, such as Prägnanz and microgenesis, are shown to be highly relevant to this theme. Natsoulas’ recent appraisal of my viewpoint has goaded me into reiterating (...) the argument for looking at a qualitative change in thought, characterizing the shift in consciousness6, as being a promising area for further development. This hypothesized change in mode of thinking is of a metaphoric—symbolic nature, what such authors as Hunt and Haskell would term symbolic cognition. I discuss the relationships among perceptual experience, symbolic cognition and state of consciousness, concluding with some comments on Natsoulas’ reservations. (shrink)

Concepts such as “symbolism” and “symbolic cognition” often remain unspecified in discussions the symbolic capacities of earlier hominins. In this paper, I use conceptual tools from phenomenology to reflect on the origins of early symbolic cognition. In particular, I discuss the possible early use of pointing gestures around the time of the earliest known stone tool industries. I argue that unlike more basic social acts such as expression, gaze following, and attention-getters, which are used by (...) extant non-human great apes, communicative pointing involves key elements that are characteristic of symbolic cognition. In particular, it involves “third order intentionality” as well as “shared practice horizons”: shared frameworks of understanding which are required for the interpretation of communicative acts whose meaning is not codified indexically or iconically in the signaling behavior. In the final part, I briefly review some indications for the use of pointing gestures around the time of the Lomekwian and Oldowan industries, as a way to sustain cooperation and possibly learning by instruction. It is suggested that pointing is more complex than is standardly acknowledged, and that it may have been an important communicative act for Early Stone Age hominins in transitioning to more fully symbolic speech capacities. (shrink)

Humans’ capacity for so-called symbolic cognition is often invoked by evolutionary theorists, and in particular archaeologists, when attempting to explain human cognitive and behavioral uniqueness. But what is meant by “symbolic cognition” is often left underspecified. In this article, I identify and discuss three different ways in which the notion of symbolic cognition might be construed, each of them quite distinct. Getting clear on the nature of symbolic cognition is a necessary first (...) step in determining what symbolic cognition might plausibly explain. (shrink)

The constructivist notion that features are purely functional is incompatible with the classical computational metaphor of mind. I suggest that the discontent expressed by Schyns, Goldstone and Thibaut about fixed-features theories of categorization reflects the growing impact of connectionism, and show how their perspective is similar to recent research on implicit learning, consciousness, and development. A hard problem remains, however: How to bridge the gap between subsymbolic and symbolic cognition.

Keeping track of what others believe is a central part of human social cognition. However, the social relevance of those beliefs can vary a great deal. Some belief attributions mostly tell us about what a person is likely to do next. Other belief attributions tell us more about a person's social identity. In this paper, I argue that we cope with this challenge by employing two distinct concepts of belief in our everyday social interactions. The epistemic concept of belief (...) is primarily used to keep track of what other people take to be true, and this informs how we predict and interpret their behaviors. The symbolic concept of belief, in contrast, is primarily used as a means of signaling one's social identity to other members of one's community. In turn, community members closely monitor each other's symbolic beliefs as a means of enforcing social norms. (shrink)

Whether computational algorithms such as latent semantic analysis (LSA) can both extract meaning from language and advance theories of human cognition has become a topic of debate in cognitive science, whereby accounts of symbolic cognition and embodied cognition are often contrasted. Albeit for different reasons, in both accounts the importance of statistical regularities in linguistic surface structure tends to be underestimated. The current article gives an overview of the symbolic and embodied cognition accounts and (...) shows how meaning induction attributed to a specific statistical process or to activation of embodied representations should be attributed to language itself. Specifically, the performance of LSA can be attributed to the linguistic surface structure, more than special characteristics of the algorithm, and embodiment findings attributed to perceptual simulations can be explained by distributional linguistic information. (shrink)

A great deal of research has focused on the question of whether or not concepts are embodied as a rule. Supporters of embodiment have pointed to studies that implicate affective and sensorimotor systems in cognitive tasks, while critics of embodiment have offered nonembodied explanations of these results and pointed to studies that implicate amodal systems. Abstract concepts have tended to be viewed as an important test case in this polemical debate. This essay argues that we need to move beyond a (...) pretheoretical notion of abstraction. Against the background of current research and theory, abstract concepts do not pose a single, unified problem for embodied cognition but, instead, three distinct problems: the problem of generalization, the problem of flexibility, and the problem of disembodiment. Identifying these problems provides a conceptual framework for critically evaluating, and perhaps improving upon, recent theoretical proposals. (shrink)

We argue that one important aspect of the “cognitive neuroscience revolution” identified by Boone and Piccinini :1509–1534. doi: 10.1007/s11229-015-0783-4, 2015) is a dramatic shift away from thinking of cognitive representations as arbitrary symbols towards thinking of them as icons that replicate structural characteristics of their targets. We argue that this shift has been driven both “from below” and “from above”—that is, from a greater appreciation of what mechanistic explanation of information-processing systems involves, and from a greater appreciation of the problems (...) solved by bio-cognitive systems, chiefly regulation and prediction. We illustrate these arguments by reference to examples from cognitive neuroscience, principally representational similarity analysis and the emergence of dynamical models as a central postulate in neurocognitive research. (shrink)

Cognitive scientists have a variety of approaches to studying cognition: experimental psychology, computer science, robotics, neuroscience, educational psychology, philosophy of mind, and psycholinguistics, to name but a few. In addition, they also differ in their approaches to cognition - some of them consider that the mind works basically like a computer, involving programs composed of abstract, amodal, and arbitrary symbols. Others claim that cognition is embodied - that is, symbols must be grounded on perceptual, motoric, and emotional (...) experience. The existence of such different approaches has consequences when dealing with practical issues such as understanding brain disorders, designing artificial intelligence programs and robots, improving psychotherapy, or designing instructional programs. The symbolist and embodiment camps seldom engage in any kind of debate to clarify their differences. This book is the first attempt to do so. It brings together a team of outstanding scientists, adopting symbolist and embodied viewpoints, in an attempt to understand how the mind works and the nature of linguistic meaning. As well as being interdisciplinary, all authors have made an attempt to find solutions to substantial issues beyond specific vocabularies and techniques. (shrink)

This paper explores a line of argument against the classical paradigm in cognitive science that is based upon properties of non-linear dynamical systems, especially in their chaotic and near-chaotic behavior. Systems of this kind are capable of generating information-rich macro behavior that could be useful to cognition. I argue that a brain operating at the edge of chaos could generate high-complexity cognition in this way. If this hypothesis is correct, then the symbolic processing methodology in cognitive science (...) faces serious obstacles. A symbolic description of the mind will be extremely difficult, and even if it is achieved to some approximation, there will still be reasons for rejecting the hypothesis that the brain is in fact a symbolic processor. (shrink)

In the first section of the article, we examine some recent criticisms of the connectionist enterprise: first, that connectionist models are fundamentally behaviorist in nature (and, therefore, non-cognitive), and second that connectionist models are fundamentally associationist in nature (and, therefore, cognitively weak). We argue that, for a limited class of connectionist models (feed-forward, pattern-associator models), the first criticism is unavoidable. With respect to the second criticism, we propose that connectionist modelsare fundamentally associationist but that this is appropriate for building models (...) of human cognition. However, we do accept the point that there are cognitive capacities for which any purely associative model cannot provide a satisfactory account. The implication that we draw from is this is not that associationist models and mechanisms should be scrapped, but rather that they should be enhanced.In the next section of the article, we identify a set of connectionist approaches which are characterized by “active symbols” — recurrent circuits which are the basis of knowledge representation. We claim that such approaches avoid criticisms of behaviorism and are, in principle, capable of supporting full cognition. In the final section of the article, we speculate at some length about what we believe would be the characteristics of a fully realized active symbol system. This includes both potential problems and possible solutions (for example, mechanisms needed to control activity in a complex recurrent network) as well as the promise of such systems (in particular, the emergence of knowledge structures which would constitute genuine internal models). (shrink)

Cognitive scientists use computational models to represent the results of their experimental work and to guide further research. Neither of these claims is particularly controversial, but the philosophical and evidentiary statuses of these models are hotly debated. To clarify the issues, I return to Newell and Simon’s 1972 exposition on the computational approach; they herald its ability to describe mental operations despite that the neuroscience of the time could not. Using work on visual imagery (cf. imagination) as a guide, I (...) examine the extent to which this holds true today. Does contemporary neuroscience contain mechanisms capable of describing experimental results in imagery? I argue that it does not, first by exploring foundational achievements in imagery research then by showing that their neural basis cannot be specified. Newell and Simon’s methodological position accordingly stands, even 50 years later. Computational — as opposed to physiological — descriptions must be retained to characterize and study mental phenomena, even as we learn high-level details of their implementation via brain data. (shrink)

This paper is the second part of the investigation. Chr. A. Crusius in the “Way to the Certainty and Adequacy of Human Knowledge” introduced the most developed alternative view to Wolffian position regarding symbolic and contemplating correlation. He preferred the contemplating cognition and tied its functioning with imagination. Kant in the “Critique of Pure Reason” brings about a terminology revolution and changes the style of the problem consideration. He turns the proceeding from F. Viet and G.W. Leibniz’s art (...) “speciosa generalis”, which was earlier thought as symbolic, into a priori figurative synthesis. Following the changes in the nature of sensibility and understanding treatment, Kant rejects the opposition of intuitive or contemplative and symbolic in favour of the following oppositions: intuitive is opposed to discursive, while the contemplation is opposed to the understanding concept. The figurative synthesis as a result of transcendental faculty of imagination instead of the former empirical imagery creates the schematic possibility of the empirical image per se. This well-developed Kant’s position unwittingly put aside Wolff’s program of reduction of the symbolic cognition to quasi-intuitive one. However, today this program can have a practical importance and enrich the problem of the cognition visibility. (shrink)

A wide range of systems appear to perform computation: what common features do they share? I consider three examples, a digital computer, a neural network and an analogue route finding system based on soap-bubbles. The common feature of these systems is that they have autonomous dynamics — their states will change over time without additional external influence. We can take advantage of these dynamics if we understand them well enough to map a problem we want to solve onto them. Programming (...) consists of arranging the starting state of a system so that the effects of the system''s dynamics on some of its variables corresponds to the effects of the equations which describe the problem to be solved on their variables. The measured dynamics of a system, and hence the computation it may be performing, depend on the variables of the system we choose to attend to. Although we cannot determine which are the appropriate variables to measure in a system whose computation basis is unknown to us I go on to discuss how grammatical classifications of computational tasks and symbolic machine reconstruction techniques may allow us to rule out some measurements of a system from contributing to computation of particular tasks. Finally I suggest that these arguments and techniques imply that symbolic descriptions of the computation underlying cognition should be stochastic and that symbols in these descriptions may not be atomic but may have contents in alternative descriptions. (shrink)

In this paper, I attempt to sketch a dialectical approach on scientific representations and their role in scientific cognition. In my understanding, scientific representations can be construed as ‘tools’ mediating scientific cognition. These ‘tools’ are products of our cognitive activity, by which we signify which features of certain objects or states of affairs should be embodied in abstractive representations of them. In such a context, I explore the merits of bringing some ideas of thinkers whose work is underestimated (...) in the relevant discussion nowadays (such as K. Marx, E.V. Ilyenkov, L.S. Vygotsky, M. Wartofsky) in dialogue with currently discussed approaches. (shrink)

We briefly review and discuss symbolic expressions of the cognitive architecture of the human mind/brain, focusing on the Quaternion, the Axis Mundi and the Tree of Life, and elaborate on a quaternary diagram that expresses a contemporary worldview. While traditional symbols contain vertical and horizontal dimensions related to transcendence and immanence, respectively, in the contemporary interpretation the vertical axis refers to diachronic processes as biological evolution and cultural history, while the horizontal axis refers to synchronic relations as the interactions (...) of individuals in society. In spite of these differences, we claim that old and new symbols are similar, expressing the cognitive architecture of the human mind/brain in the world of experience. (shrink)

This paper explores some of the constructive dimensions and specifics of human theoretic cognition, combining perspectives from (Husserlian) genetic phenomenology and distributed cognition approaches. I further consult recent psychological research concerning spatial and numerical cognition. The focus is on the nexus between the theoretic development of abstract, idealized geometrical and mathematical notions of space and the development and effective use of environmental cognitive support systems. In my discussion, I show that the evolution of the theoretic cognition (...) of space apparently follows two opposing, but in truth, intrinsically aligned trajectories. On the epistemic plane, which is the main focus of Husserl’s genetic phenomenological investigations, theoretic conceptions of space are progressively constituted by way of an idealizing emancipation of spatial cognition from the concrete, embodied intentionality underlying the human organism’s perception of space. As a result of this emancipation, it ultimately becomes possible for the human mind to theoretically conceive of and posit space as an ideal entity that is universally geometrical and mathematical. At the same time, by synthesizing a range of literature on spatial and mathematical cognition, I illustrate that for the theoretic mind to undertake precisely this emancipating process successfully, and further, for an ideal and objective notion of geometrical and mathematical space to first of all become fully scientifically operative, the cognitive support provided by a range of specific symbolic technologies is central. These include lettered diagrams, notation systems, and more generally, the technique of formalization and require for their functioning various cognitively efficacious types of embodiment. Ultimately, this paper endeavors to understand the specific symbolic-technological dimensions that have been instrumental to major shifts in the development of idealized, scientific conceptions of space. The epistemic characteristics of these shifts have been previously discussed in genetic phenomenology, but without devoting sufficient attention to the constructive role of symbolic technologies. At the same time, this paper identifies some of the irreducible phenomenological and epistemic dimensions that characterize the functioning of the historically situated, embodied and distributed theoretic mind. (shrink)

By providing symbolic (operates by means of signs) and intuitive (operates without signs) types of cognition, G.W. Leibniz in the “Reasoning about cognition, truth and ideas” laid the foundation for the problem of visibility discussions in 18th century. Proceeding from Leibniz’s ideas, Chr. Wolff in the “German metaphysics” built a detailed doctrine about figurative and contemplating cognition, giving priority in the field of application and the degree of clarity to the first type. Wolff’s doctrine almost immediately (...) became classic and found a lot of supporters. J.G. Darjes and G.F. Meier moved the metaphysical distinction of cognition distinctions to logic. A.G. Baumgarten in the “Metaphysics” offered a new criterion of symbolic and intuitive cognition distinction. J.N. Tetens scrutinized the opposition of symbolic and contemplating cognition from the point of a priori and a posteriori opposition. J.H. Lambert in the “New Organon” brings the interest back to the figurative cognition. (shrink)

I propose here an image of knowledge based on the concept of symbol: according to it, the relation of representation that constituting cognition is a symbolization. It is postulated that both the representing conceptual model, i.e. a pre-linguistic entity acquired in cognition, and the true sentence it generates are of symbolic and not of mirroring character. The symbolic nature of cognition carries dialectical tension. We have at our disposal conceptual models and true sentences which symbolically (...) represent reality. However, it is not possible to lift the symbolic disguise over knowledge, because precisely this disguise is its essence. Reality appears only as symbolically, nonimitatively encoded. The proposed here symbolic realism rejects the traditional adopted dichotomy between, on one side, realism and the absence of the subject’s factors in the cognitive result, and, on the other, idealism and the subject as a factor which is viewed as inevitably leading to the idealistic nature of knowledge. (shrink)

The ability to anticipate team members' actions enables joint action towards a common goal. Task knowledge and mental simulation allow for anticipating other agents' actions and for making inferences about their underlying mental representations. In human–AI teams, providing AI agents with anticipatory mechanisms can facilitate collaboration and successful execution of joint action. This paper presents a computational cognitive model demonstrating mental simulation of operators' mental models of a situation and anticipation of their behavior. The work proposes two successive steps: (1) (...) A hierarchical cluster algorithm is applied to recognize patterns of behavior among pilots. These behavioral clusters are used to derive commonalities in situation models from empirical data (N = 13 pilots). (2) An ACT-R (adaptive control of thought - rational) cognitive model is implemented to mentally simulate different possible outcomes of action decisions and timing of a pilot. model tracing of ACT-R allows following up on operators' individual actions. Two models are implemented using the symbolic representations of ACT-R: one simulating normative behavior and the other by simulating individual differences and using subsymbolic learning. Model performance is analyzed by a comparison of both models. Results indicate the improved performance of the individual differences over the normative model and are discussed regarding implications for cognitive assistance capable of anticipating operator behavior. (shrink)

In previous work, I have looked in detail at the capacity and the limits of the linguistics model as applied to gene expression. The recent use of a primitive applied linguistic model in Apple's SIRI system allows further analysis. In particular, the failings of this system resemble those of the HGP; the model used also helps point out the shortcomings of the concept of the "gene". This is particularly urgent as we are entering an era of applied biology in the (...) absence of theory, and indeed an era with a near-epidemic of retracted papers. There are a few workarounds proposed. One is to add to the nascent field of biosemiotics a more explicit concern with syntax. At the time of writing, Apple is being sued for false advertising of its iphone 4s, with the associated claim that apple had solved many of the problems of natural language processing by computer . The system was bought by Apple from a company called SIRI, and in turn was based on the notion, trumpeted by the prior art in a company called Dejima, that nlpbc could be done by keywords alone. Yet the hype resembles nothing so much as the misrepresentation of the Human Genome Project fed to the media in the glory days at the beginning of this millennium, and it says a lot for the status of scientists in society that they have avoided Apple's fate. In this paper, a short review of several current themes in theoretical and applied biology is first proposed. Then the tensions implicit in the notion that the "gene" is simultaneously to be identified as a unit of inheritance and spatially located over spatially well-defined nucleotides is explored and the notion is found to be incoherent. An expanded notion of inheritance is proposed in the context of a focus on inheritance as necessarily involving species, population and organism over time. While it is premature to talk about a paradigm shift, it is certainly arguable that biology urgently needs a sophisticated theory of how symbols work substantially more sophisticated than that implicit in the HGP; Biosemiotics affords a framework in which this might be tried. Indeed, as this paper concludes, there may yet be room for a "Bionoetics", a perspective in which biological explanation can be extended to include cognition in all its forms. Finally, a working sketch of a modeling environment written in LISP, one that shows promise in reflecting the complexities discussed in the paper, is included. Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;}. (shrink)

People often solve spatially presented cognitive problems more easily than their nonspatial counterparts. We explain this phenomenon by characterizing space as an inter-modality that provides common structure to different specific perceptual modalities. The usefulness of spatial structure for knowledge processing on different levels of granularity and for interaction between internal and external processes is described. Map representations are discussed as examples in which the usefulness of spatially organized symbols is particularly evident. External representations and processes can enhance internal representations and (...) processes effectively when the same structures and principles can be implicitly assumed. (shrink)

In this paper, I attempt to sketch a dialectical approach on scientific representations and their role in scientific cognition. In my understanding, scientific representations can be construed as ‘tools’ mediating scientific cognition. These ‘tools’ are products of our cognitive activity, by which we signify which features of certain objects or states of affairs should be embodied in abstractive representations of them. In such a context, I explore the merits of bringing some ideas of thinkers whose work is underestimated (...) in the relevant discussion nowadays in dialogue with currently discussed approaches. (shrink)

This book endeavors to fill the conceptual gap in theorizing about embodied cognition. The theories of mind and cognition which one could generally call "situated" or "embodied cognition" have gained much attention in the recent decades. However, it has been mostly phenomenology, which has served as a philosophical background for their research program. The main goal of this book is to bring the philosophy of classical American pragmatism firmly into play. Although pragmatism has been arguably the first (...) intellectual current which systematically built its theories of knowledge, mind and valuation upon the model of a bodily interaction between an organism and its environment, as the editors and authors argue, it has not been given sufficient attention in the debate and, consequently, its conceptual resources for enriching the embodied mind project are far from being exhausted. In this book, the authors propose concrete subject-areas in which the philosophy of pragmatism can be of help when dealing with particular problems the philosophy of the embodied mind nowadays faces - a prominent example being the inevitable tension between bodily situatedness and the potential universality of symbolic meaning. (shrink)

This paper proposes how various disciplinary theories of cognition may be combined into a unifying, sub-symbolic, computational theory of cognition. The following theories are considered for integration: psychological theories, including the theory of event coding, event segmentation theory, the theory of anticipatory behavioral control, and concept development; artificial intelligence and machine learning theories, including reinforcement learning and generative artificial neural networks; and theories from theoretical and computational neuroscience, including predictive coding and free energy-based inference. In the light (...) of such a potential unification, it is discussed how abstract cognitive, conceptualized knowledge and understanding may be learned from actively gathered sensorimotor experiences. The unification rests on the free energy-based inference principle, which essentially implies that the brain builds a predictive, generative model of its environment. Neural activity-oriented inference causes the continuous adaptation of the currently active predictive encodings. Neural structure-oriented inference causes the longer term adaptation of the developing generative model as a whole. Finally, active inference strives for maintaining internal homeostasis, causing goal-directed motor behavior. To learn abstract, hierarchical encodings, however, it is proposed that free energy-based inference needs to be enhanced with structural priors, which bias cognitive development towards the formation of particular, behaviorally suitable encoding structures. As a result, it is hypothesized how abstract concepts can develop from, and thus how they are structured by and grounded in, sensorimotor experiences. Moreover, it is sketched-out how symbol-like thought can be generated by a temporarily active set of predictive encodings, which constitute a distributed neural attractor in the form of an interactive free-energy minimum. The activated, interactive network attractor essentially characterizes the semantics of a concept or a concept composition, such as an actual or imagined situation in our environment. Temporal successions of attractors then encode unfolding semantics, which may be generated by a behavioral or mental interaction with an actual or imagined situation in our environment. Implications, further predictions, possible verification and falsifications, as well as potential enhancements into a fully spelled-out unified theory of cognition are discussed at the end of the paper. (shrink)

"In his Phenomenology of Cognition, Cassirer provides a comprehensive and systematic account of the dynamic process involved in the whole of human culture as it progresses from the world of myth and its feeling of social belonging to the highest abstractions of mathematics, logic and theoretical physics. Cassirer engages with the most sophisticated and cutting-edge work in fields ranging from ethnology to classics, egyptology and assyriology to ethology, brain science and psychology to logic, mathematics and theoretical physics. His command (...) of philosophy, literature, and the arts is superb. Echoing his work on Kant, Cassirer begins ThePhilosophy of Symbolic Formswith the problem posed by the meaning of being for philosophy since Plato. But Cassirer also shows that this problem gains new significance with Kant and with the development of modern culture. Cassirer weaves his conception of the development of knowledge into a broadly Kantian and German idealist dynamic-historical conception of significance and of experience that refuses to accept a fundamental opposition between literary, philosophical and scientific culture. In consequence of his great vision grounded in careful reflection and argument, Cassirer's systematic conception of the Copernican cosmopolitan-cosmological revolution is still philosophically and scientifically unmatched in contemporary philosophy on both sides of the Atlantic and of the Pacific." - Pierre Keller, Professor of Philosophy, University of California, Riverside, USA. This new translation makes Cassirer's seminal work available to a new generation of scholars. Each volume includes an introduction by Steve Lofts, a foreword by Peter Gordon, a glossary of key terms, and an index. Steve Lofts is Professor of Philosophy at King's University College, Canada. He is the translator of Cassirer's The Logic of the Cultural Sciences and The Warburg Years : Essays on Language, Art, Myth, and Technology. (shrink)

Connectionism and computationalism are currently vying for hegemony in cognitive modeling. At first glance the opposition seems incoherent, because connectionism is itself computational, but the form of computationalism that has been the prime candidate for encoding the "language of thought" has been symbolic computationalism (Dietrich 1990, Fodor 1975, Harnad 1990c; Newell 1980; Pylyshyn 1984), whereas connectionism is nonsymbolic (Fodor & Pylyshyn 1988, or, as some have hopefully dubbed it, "subsymbolic" Smolensky 1988). This paper will examine what is and is (...) not a symbol system. A hybrid nonsymbolic/symbolic system will be sketched in which the meanings of the symbols are grounded bottom-up in the system's capacity to discriminate and identify the objects they refer to. Neural nets are one possible mechanism for learning the invariants in the analog sensory projection on which successful categorization is based. "Categorical perception" (Harnad 1987a), in which similarity space is "warped" in the service of categorization, turns out to be exhibited by both people and nets, and may mediate the constraints exerted by the analog world of objects on the formal world of symbols. (shrink)

Computation is interpretable symbol manipulation. Symbols are objects that are manipulated on the basis of rules operating only on theirshapes, which are arbitrary in relation to what they can be interpreted as meaning. Even if one accepts the Church/Turing Thesis that computation is unique, universal and very near omnipotent, not everything is a computer, because not everything can be given a systematic interpretation; and certainly everything can''t be givenevery systematic interpretation. But even after computers and computation have been successfully distinguished (...) from other kinds of things, mental states will not just be the implementations of the right symbol systems, because of the symbol grounding problem: The interpretation of a symbol system is not intrinsic to the system; it is projected onto it by the interpreter. This is not true of our thoughts. We must accordingly be more than just computers. My guess is that the meanings of our symbols are grounded in the substrate of our robotic capacity to interact with that real world of objects, events and states of affairs that our symbols are systematically interpretable as being about. (shrink)

There has been a long-standing debate between symbolicists and connectionists concerning the nature of representation used by human cognizers. In general, symbolicist commitments have allowed them to provide superior models of high-level cognitive function. In contrast, connectionist distributed representations are preferred for providing a description of low-level cognition. The development of Holographic Reduced Representations (HRRs) has opened the possibility of one representational medium unifying both low-level and high-level descriptions of cognition. This paper describes the relative strengths and weaknesses (...) of symbolic and distributed representations. HRRs are shown to capture the important strengths of both types of representation. These properties of HRRs allow a rebuttal of Fodor and McLaughlin's (1990) criticism that distributed representations are not adequately structure sensitive to provide a full account of human cognition. (shrink)

This paper surveys applications of logical methods in the cognitive sciences. Special attention is paid to non-monotonic logics and complexity theory. We argue that these particular tools have been useful in clarifying the debate between symbolic and connectionist models of cognition.

The epistemic stances of both Whitehead and the Book of Changes are founded on the assumption that process is reality; there are important resonances with respect to perception, meaning and significance. Such a process-oriented approach is productive for developing non-representational and non-dualistic theories in the fields of epistemology, philosophy of language and philosophy of mind. An exploration of these resonances will further provide an appropriate foundation for dialogue between the philosophy of the Book of Changes and that of contemporary Euro-American (...) philosophy. The important differences between the Book of Changes and Whiteheadian philosophy will also become apparent. (shrink)

This paper presents work in progress on artificial intelligence in medicine (AIM) within the larger context of cognitive science. It introduces and develops the notion ofemergence both as an inevitable evolution of artificial intelligence towards machine learning programs and as the result of a synergistic co-operation between the physician and the computer. From this perspective, the emergence of knowledge takes placein fine in the expert's mind and is enhanced both by computerised strategies of induction and deduction, and by software abilities (...) to dialogue, co-operate and function as a cognitive extension of the physician's intellectual capabilities. The proposed methodology gives the expert a prominent role which consists, first, of faithfully enunciating the descriptive features of his medical knowledge, thus giving the computer a precise description of his own perception of basic medicine, and secondly, of painstakingly gathering patients into computerised case bases which simulate exhaustive long-term memory. The AI capacities for knowledge elaboration are then triggered, giving rise to mathematically optimal diagnoses, prognoses, or treatment protocols which the physician may then evaluate, accept, reject, or adapt at his convenience, and finally append to a knowledge base. The idea of emergence embraces many issues concerning the purpose and intent of artificial intelligence in medical practice. Particularly, we address the representation problem as it is raised by classical decisional knowledge-based systems, and develop the notions of classifiers and hybrid systems as possible answers to this problem. Finally, since the whole methodology touches the problem of technological investment in health care, now inherent in modern medical practice, some ethical considerations accompany the exposé. (shrink)

As this foreword is written, at the dawn of the 21st Century, the cognitive sciences are in epistemological ferment. The exuberant optimism of the late 20th-Century adaptationist programme has, itself, started to fragment like the many fingers of a wave against the implacable shore of empirical reality. Dramatic new directions in the philosophy of mind and in developmental psychology are beginning to mature. This special issue, Pointing: Where Embodied Cognition meets the Symbolic Mind, edited by Massimiliano Cappuccio, brings (...) together in one volume an incendiary mix of the emerging generation of philosophers and language researchers, who bring their diverse perspectives to moor on one of the most fascinating phenomena in human development: the ability to co-orient in both space and time to a common focus with what seems, on the face of it, to be a simple pointing gesture. The emerging significance of research and analysis pertaining to pointing reflects a recent phase shift in the sciences concerned with mind and behaviour. To put these innovations in context, it might be worthwhile to review the sweeping upheavals that have recently occurred in the conceptual bedrocks of psychology and the philosophy of language. (shrink)

Recent experimental evidence from developmental psychology and cognitive neuroscience indicates that humans are equipped with unlearned elementary mathematical skills. However, formal mathematics has properties that cannot be reduced to these elementary cognitive capacities. The question then arises how human beings cognitively deal with more advanced mathematical ideas. This paper draws on the extended mind thesis to suggest that mathematical symbols enable us to delegate some mathematical operations to the external environment. In this view, mathematical symbols are not only used to (...) express mathematical concepts—they are constitutive of the mathematical concepts themselves. Mathematical symbols are epistemic actions, because they enable us to represent concepts that are literally unthinkable with our bare brains. Using case-studies from the history of mathematics and from educational psychology, we argue for an intimate relationship between mathematical symbols and mathematical cognition. (shrink)