Prior to the twentieth century, theories of knowledge were inherently perceptual. Since then, developments in logic, statis- tics, and programming languages have inspired amodal theories that rest on principles fundamentally different from those underlying perception. In addition, perceptual approaches have become widely viewed as untenable because they are assumed to implement record- ing systems, not conceptual systems. A perceptual theory of knowledge is developed here in the context of current cognitive science and neuroscience. During perceptual experience, association areas in the (...) brain capture bottom-up patterns of activation in sensory-motor areas. Later, in a top-down manner, association areas partially reactivate sensory-motor areas to implement perceptual symbols. The stor- age and reactivation of perceptual symbols operates at the level of perceptual components – not at the level of holistic perceptual expe- riences. Through the use of selective attention, schematic representations of perceptual components are extracted from experience and stored in memory (e.g., individual memories of green, purr, hot). As memories of the same component become organized around a com- mon frame, they implement a simulator that produces limitless simulations of the component (e.g., simulations of purr). Not only do such simulators develop for aspects of sensory experience, they also develop for aspects of proprioception (e.g., lift, run) and introspec- tion (e.g., compare, memory, happy, hungry). Once established, these simulators implement a basic conceptual system that represents types, supports categorization, and produces categorical inferences. These simulators further support productivity, propositions, and ab- stract concepts, thereby implementing a fully functional conceptual system. Productivity results from integrating simulators combinato- rially and recursively to produce complex simulations. Propositions result from binding simulators to perceived individuals to represent type-token relations. Abstract concepts are grounded in complex simulations of combined physical and introspective events. Thus, a per- ceptual theory of knowledge can implement a fully functional conceptual system while avoiding problems associated with amodal sym- bol systems. Implications for cognition, neuroscience, evolution, development, and artificial intelligence are explored. (shrink)

On the occasion of a first conference on Cognitive Science, it seems appropriate to review the basis of common understanding between the various disciplines. In my estimate, the most fundamental contribution so far of artificial intelligence and computer science to the joint enterprise of cognitive science has been the notion of a physical symbol system, i.e., the concept of a broad class of systems capable of having and manipulating symbols, yet realizable in the physical universe. The notion of (...) symbol so defined is internal to this concept, so it becomes a hypothesis that this notion of symbols includes the symbols that we humans use every day of our lives. In this paper we attempt systematically, but plainly, to lay out the nature of physical symbol systems. Such a review is in ways familiar, but not thereby useless. Restatement of fundamentals is an important exercise. (shrink)

RésuméSelon une thèse holistique sur les symboles, un symbole nepeut exister isolément mais doit faire partie d'un système symbolique. Une opinion, elle aussi plausible, veut que les systémes symboliques émergent graduellement chez un individu, un groupe ou une espéce. Le problème c'est qu'on voit mal, si le holisme des systémes symboliques tient, comment un système symbolique peut émerger graduellement, du moins pour la première fois. Ce n'est possible, semble-t-il, que si être un symbole est affaire de degré, thèse au départ (...) problématique. Cet article explique comment être un symbole cognitif peut après tout être affaire de degré. L'intuition contraire vient de ce que le processus d' interprétation nous force au tout ou rien, ce qui laisse unjeu dans la façon dont le matériel sous-jacent réalise les symboles à des degres divers. Les travaux de Daniel Dennett sont à cet égard éclairants. Le holisme vautpour les symboles tels qu'ils sont interprétés, tandis que le gradualisme vaut pour la façon dont le matériel sous-jacent réalise les symboles. (shrink)

In his target article, Barsalou cites current work on emotion theory but does not explore its relevance for this project. The connection is worth pursuing, since there is a plausible case to be made that emotions form a distinct symbolic information processing system of their own. On some views, that system is argued to be perceptual: a direct connection with Barsalou's perceptual symbol systems theory. Also relevant is the hypothesis that there may be different modular subsystems within (...) emotion and the perennial tension between cognitive and perceptual theories of emotion. (shrink)

This short paper grew out of an observation—made in the course of a larger research project—of a surprising convergence between, on the one hand, certain themes in the work of Mary Hesse and Nelson Goodman in the 1950/60s and, on the other hand, recent work on the representational resources of science, in particular regarding model-based representation. The convergence between these more recent accounts of representation in science and the earlier proposals by Hesse and Goodman consists in the recognition that, in (...) order to secure successful representation in science, collective representational resources must be available. Such resources may take the form of (amongst others) mathematical formalisms, diagrammatic methods, notational rules, or—in the case of material models—conventions regarding the use and manipulation of the constituent parts. More often than not, an abstract characterization of such resources tells only half the story, as they are constituted equally by the pattern of (practical and theoretical) activities—such as instances of manipulation or inference—of the researchers who deploy them. In other words, representational resources need to be sustained by a social practice; this is what renders them collective representational resources in the first place. (shrink)

The concept of representation has become almost inextricably bound to the concept of symbol systems. the concepts is nowhere more prevalent than in descriptions of "internal representations." These representations are thought to occur in an internal symbol system that allows the brain to store and use information. In this paper we explore a different approach to understanding psychological processes, one that retains a commitment to representations and computations but that is not based on the idea that information (...) must be stored and manipulated in symbol systems. In particular, we suggest that the notion of a symbol system as currently understood construes psychological processes in terms of a specific type of computational system, in which a control function "reads," "interprets," and manipulates discrete entities called "symbols." We argue that other types of computational systems may provide a more appropriate characterization of psychological processes. One implication of our argument is the need to consider the constraints placed on computational theories in psychology by the nature of the computing device itself, the human brain. Perhaps surprisingly, this implication leads us to the conclusion that a "functionalist" conception of psychological processes (discussed below) does not entail that physiology is irrelevant to psychology, as has been maintained by prominent adherents of the symbol-systems approach. (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)

The aim of this work is to develop a comparative analysis of the discursive structures that underlie the socialized formation of the interpretative paradigms of reality. We analyse how both political ideologies and the so-called “conspiracy theories” can be understood starting from the structure and functioning of Marc Augè's ideo-logic, namely the systemic-discursive device that defines the field of all possible sentences defining the real. -/- .

Classic of Changes is a Chinese cultural classic born more than 3000 years ago. Its profound philosophical thoughts and the use of divination have brought Classic of Changes to a strong oriental mysticism. The view of the heaven and man of yin and yang and the five elements states of Classic of Changes are completely different from the Western elemental theory of ancient Greece. The latter gave birth to classical and modern scientific theories, and the yin and yang and the (...) eight trigrams symbol has become synonymous with oriental mysticism. In fact, the cosmology of the Holism of Classic of Changes is a precious scientific heritage of mankind. The axiomatization of the symbolic formal system of Classic of Changes aims to unveil the veil of oriental mysticism and provide oriental wisdom for the development of modern science. Transforming the symbolic system of Classic of Changes into a formal axiom system is the crystallization of the fusion of wisdom between the East and the West. The axiomatization of the symbolic formal system of Classic of Changes shows that the oriental and the western scientific tradition harmony but not sameness and there is no conflict. Classic of Changes can also be interpreted by the axiomatic system like Euclid’s Elements. The main contribution of this paper is that the author skillfully uses mathematical language to formulate the system of Classic of Changes, reconstructs the ideological system of Classic of Changes with the axiomatic method and realizes the scientificalization of Chinese classical natural philosophy. The formal axiom system of Classic of Changes may give us such a revelation: the gap between the oriental and western scientific traditions is mainly in the axiomatization, but the lack of oriental scientific tradition may be the bottleneck of the development of modern science. (shrink)

One holistic thesis about symbols is that a symbol cannot exist singly, but only as apart of a symbol system. There is also the plausible view that symbol systems emerge gradually in an individual, in a group, and in a species. The problem is that symbol holism makes it hard to see how a symbol system can emerge gradually, at least if we are considering the emergence of a first symbol system. (...) The only way it seems possible is if being a symbol can be a matter of degree, which is initially problematic. This article explains how being a cognitive symbol can be a matter of degree after all. The contrary intuition arises from the way a process of interpretation forces an all-or-nothing character on symbols, leaving room for underlying material to realize symbols to different degrees in a way that Daniel Dennett’s work can help illuminate. Holism applies to symbols as interpreted, while gradualism applies to how the underlying material realizes symbols.Selon une thèse holistique sur les symboles, un symbole ne peut exister isolément mais doit faire partie d’un systéme symbolique. Une opinion, elle aussi plausible, veut que les systèmes symboliques émergent graduellement chez un individu, un groupe ou une espèce. Le problème c’est qu’on voit mal, si le holisme des systèmes symboliques tient, comment un système symbolique peut émerger graduellement, du moins pour la première fois. Ce n’est possible, semble-t-il, que si être un symbole est affaire de degré, thèse au départ problématique. Cet article explique comment être un symbole cognitif peut après tout être affaire de degré. L’intuition contraire vient de ce que le processus d’interprétation nous force au tout ou rien, ce qui laisse un jeu dans la façon dont le matériel sous-jacent réalise les symboles à des degrés divers. Les travaux de Daniel Dennett sont à cet égard éclairants. Le holisme vaut pour les symboles tels qu’ils sont interprétés, tandis que le gradualisme vaut pour la façon dont le matériel sous-jacent réalise les symboles. (shrink)

Abduction is or subsumes a process of inference. It entertains possible hypotheses and it chooses hypotheses for further scrutiny. There is a large literature on various aspects of non-symbolic, subconscious abduction. There is also a very active research community working on the symbolic (logical) characterisation of abduction, which typically treats it as a form of hypothetico-deductive reasoning. In this paper we start to bridge the gap between the symbolic and sub-symbolic approaches to abduction. We are interested in benefiting from developments (...) made by each community. In particular, we are interested in the ability of non-symbolic systems (neural networks) to learn from experience using efficient algorithms and to perform massively parallel computations of alternative abductive explanations. At the same time, we would like to benefit from the rigour and semantic clarity of symbolic logic. We present two approaches to dealing with abduction in neural networks. One of them uses Connectionist Modal Logic and a translation of Horn clauses into modal clauses to come up with a neural network ensemble that computes abductive explanations in a top-down fashion. The other combines neural-symbolic systems and abductive logic programming and proposes a neural architecture which performs a more systematic, bottom-up computation of alternative abductive explanations. Both approaches employ standard neural network architectures which are already known to be highly effective in practical learning applications. Differently from previous work in the area, our aim is to promote the integration of reasoning and learning in a way that the neural network provides the machinery for cognitive computation, inductive learning and hypothetical reasoning, while logic provides the rigour and explanation capability to the systems, facilitating the interaction with the outside world. Although it is left as future work to determine whether the structure of one of the proposed approaches is more amenable to learning than the other, we hope to have contributed to the development of the area by approaching it from the perspective of symbolic and sub-symbolic integration. (shrink)

Classical cognitive science assumes that intelligently behaving systems must be symbol processors that are implemented in physical systems such as brains or digital computers. By contrast, connectionists suppose that symbol manipulating systems could be approximations of neural networks dynamics. Both classicists and connectionists argue that symbolic computation and subsymbolic dynamics are incompatible, though on different grounds. While classicists say that connectionist architectures and symbol processors are either incompatible or the former are mere implementations of the latter, connectionists (...) reply that neural networks might be incompatible with symbol processors because the latter cannot be implementations of the former. In this contribution, the notions of 'incompatibility' and 'implementation' will be criticized to show that they must be revised in the context of the dynamical system approach to cognitive science. Examples for implementations of symbol processors that are incompatible with respect to contextual topologies will be discussed. (shrink)

Vera & Simon (1993a) have argued that the theories and methods known as situated action or situativity theory are compatible with the assumptions and methodology of the physical symbol systems hypothesis and do not require a new approach to the study of cognition. When the central criterion of computational universality is added to the loose definition of a symbol system which Vera and Simon provide, it becomes apparent that there are important incompatibilities between the two approaches such (...) that situativity theory cannot be subsumed within the symbol systems approach. Symbol systems and situativity theoretic approaches are, and should be seen to be, competing approaches to the study of cognition. (shrink)

We apply to the art of calligraphy some of the semiotic concepts developed by Nelson Goodman. While this framework cannot describe everything that is interesting and valuable about specific calligraphic traditions, we argue that it can nonetheless elegantly capture some distinctive features of calligraphy and of its position among other major art forms.

Although Barsalou is right in identifying the importance of perceptual symbols as a means of carrying certain kinds of content, he is wrong in playing down the inferential resources available to amodal symbols. I argue that the case for perceptual symbol systems amounts to a false dichotomy and that it is feasible to help oneself to both kinds of content as extreme ends on a content continuum. The continuum thesis I advance argues for the inferential content at one end (...) and perceptual content at the other. In between the extremes, symbols might have aspects that are either perceptual or propositional-linguistic in character. I argue that this way of characterising the issue preserves the good sense of Barsalou's recognition of perceptual representations and yet avoids the tendency to minimise the gains won with symbolic representations vital to contemporary cognitive science. (shrink)

Abduction is or subsumes a process of inference. It entertains possible hypotheses and it chooses hypotheses for further scrutiny. There is a large literature on various aspects of non-symbolic, subconscious abduction. There is also a very active research community working on the symbolic (logical) characterisation of abduction, which typically treats it as a form of hypothetico-deductive reasoning. In this paper we start to bridge the gap between the symbolic and sub-symbolic approaches to abduction. We are interested in benefiting from developments (...) made by each community. In particular, we are interested in the ability of non-symbolic systems (neural networks) to learn from experience using efficient algorithms and to perform massively parallel computations of alternative abductive explanations. At the same time, we would like to benefit from the rigour and semantic clarity of symbolic logic. We present two approaches to dealing with abduction in neural networks. One of them uses Connectionist Modal Logic and a translation of Horn clauses into modal clauses to come up with a neural network ensemble that computes abductive explanations in a top-down fashion. The other combines neural-symbolic systems and abductive logic programming and proposes a neural architecture which performs a more systematic, bottom-up computation of alternative abductive explanations. Both approaches employ standard neural network architectures which are already known to be highly effective in practical learning applications. Differently from previous work in the area, our aim is to promote the integration of reasoning and learning in a way that the neural network provides the machinery for cognitive computation, inductive learning and hypothetical reasoning, while logic provides the rigour and explanation capability to the systems, facilitating the interaction with the outside world. Although it is left as future work to determine whether the structure of one of the proposed approaches is more amenable to learning than the other, we hope to have contributed to the development of the area by approaching it from the perspective of symbolic and sub-symbolic integration. (shrink)

Nelson Goodman’s theory of symbol systems expounded in his Languages of Art has been frequently criticized on many counts. Yet it exerts a strong influence and is treated as one of the major twentieth-century theories on the subject.While many of Goodman’s controversial theses are criticized, the technical notions he used to formulate them seem to have been treated as neutral tools. One such technical notion is that of the density of symbol systems. This serves to distinguish linguistic symbols (...) from pictorial representations and is a crucial part of Goodman’s explanation of what constitutes aesthetic experience. Thus its significance for Goodman’s theory is fundamental.The aim of this paper is a detailed, logical analysis of this notion. It turns out that Goodman’s definition is highly problematic and cannot be applied to symbol systems in the way Goodman envisaged. To conclude, Goodman’s theory is problematic not just because of its controversial theses but also because of logical problems with the technical notions used at its very core. Hence the controversial claims are not simply contestable, but inaccurately expressed. (shrink)

After reviewing the papers in this special issue, I must conclude that brains are not syntactic engines, but control systems that orient to biological, interindividual, and cultural norms. By themselves, syntactic constraints both underdetermine and overdetermine cognitive operations. So, rather than serving as the basis for general cognition, they are just another kind of empirically acquired constraint. In humans, symbols emerge from a particular sensorimotor activity through a process of contextual broadening that depends on the coordination of conscious and nonconscious (...) processing. This process provides the representational freedom and stability that constitute the human brain’s solution to the frame problem and symbol grounding problem. Symbol formation and grounding is an ongoing process of generalising constraints from particular contexts, selectively enlisting their use, and re-automating them. This process is central to the self-creation of a language-using person with beliefs, agency, and identity. (shrink)

Human cognition is striking in its brilliance and its adaptability. How do we get that way? How do we move from the nearly helpless state of infants to the cognitive proficiency that characterizes adults? In this paper I argue, first, that analogical ability is the key factor in our prodigious capacity, and, second, that possession of a symbol system is crucial to the full expression of analogical ability.

Stevan Harnad and I seem to be thinking about many of the same issues. Sometimes we agree, sometimes we don't; but I always find his reasoning refreshing, his positions sensible, and the problems with which he's concerned to be of central importance to cognitive science. His "Grounding Symbols in the Analog World with Neural Nets" (= GS) is no exception. And GS not only exemplifies Harnad's virtues, it also provides a springboard for diving into Harnad- Bringsjord terrain.

Because intelligent agents employ physically embodied cognitive systems to reason about the world, their cognitive abilities are constrained by the laws of physics. Scientists have used digital computers to develop and validate theories of physically embodied cognition. Computational theories of intelligence have advanced our understanding of the nature of intelligence and have yielded practically useful systems exhibiting some degree of intelligence. However, the view of cognition as algorithms running on digital computers rests on implicit assumptions about the physical world that (...) are incorrect. Recently, the view is emerging of computing systems as goal-directed agents, evolving during problem solving toward improved world models and better task performance. A full realization of this vision requires a new logic for computing that incorporates learning from experience as an intrinsic part of the logic, and that permits full exploitation of the quantum nature of the physical world. This paper proposes a theory of physically embodied cognitive agents founded upon first-order logic, Bayesian decision theory, and quantum physics. An abstract architecture for a physically embodied cognitive agent is presented. The cognitive aspect is represented as a Bayesian decision theoretic agent; the physical aspect is represented as a quantum process; and these aspects are related through von Neumann’s principle of psycho-physical parallelism. Alternative metaphysical positions regarding the meaning of quantum probabilities and the role of efficacious choices by agents are discussed in relation to the abstract agent architecture. The concepts are illustrated with an extended example from the domain of science fiction. (shrink)

Mental representations have continuous as well as discrete, combinatorial properties. For example, while predominantly discrete, phonological representations also vary continuously; this is reflected by gradient effects in instrumental studies of speech production. Can an integrated theoretical framework address both aspects of structure? The framework we introduce here, Gradient Symbol Processing, characterizes the emergence of grammatical macrostructure from the Parallel Distributed Processing microstructure (McClelland, Rumelhart, & The PDP Research Group, 1986) of language processing. The mental representations that emerge, Distributed (...) class='Hi'>Symbol Systems, have both combinatorial and gradient structure. They are processed through Subsymbolic Optimization–Quantization, in which an optimization process favoring representations that satisfy well-formedness constraints operates in parallel with a distributed quantization process favoring discrete symbolic structures. We apply a particular instantiation of this framework, λ-Diffusion Theory, to phonological production. Simulations of the resulting model suggest that Gradient Symbol Processing offers a way to unify accounts of grammatical competence with both discrete and continuous patterns in language performance. (shrink)

It has been suggested that iconic graphical signs evolve into symbolic graphical signs through repeated usage. This article reports a series of interactive graphical communication experiments using a ‘pictionary’ task to establish the conditions under which the evolution might occur. Experiment 1 rules out a simple repetition based account in favor of an account that requires feedback and interaction between communicators. Experiment 2 shows how the degree of interaction affects the evolution of signs according to a process of grounding. Experiment (...) 3 confirms the prediction that those not involved directly in the interaction have trouble interpreting the graphical signs produced in Experiment 1. On the basis of these results, this article argues that icons evolve into symbols as a consequence of the systematic shift in the locus of information from the sign to the users' memory of the sign's usage supported by an interactive grounding process. (shrink)

This book is a broad introduction for the general reader to the study of language. Only the first half of the book deals with linguistics proper: phonetics, phonemics, morphology and syntax, problems of meaning, linguistic change, and the classification of languages. The author aims to present only the basic and universally accepted results in each of these areas, and avoids controversial matters as much as possible. Where differences among linguists do exist, he indicates them without elaborating them. The second part (...) of the book is concerned with peripheral matters; such as the place of language in daily life, the problems of learning and translating languages, the employment of mechanical devices in phonetics, translation and recording, the structure of symbolic systems and their application in communications. Each topic is treated concisely, but with clarity, liveliness, and humor. The reader acquires not only a large body of basic information, but also a sense of the importance of language and the study of language.--T. D. Z. (shrink)

The target article provides a convincing argument that nonhuman animals cannot process role-governed rules, relational schemas, and so on, in a human-like fashion. However, actual human performance is often more similar to that of nonhuman animals than Penn et al. admit. The kind of rule-governed performance the authors take for granted may rely to a substantial degree on language on external symbol systems such as those provided by language and culture.

The goal of forming a science of intentional behavior requires a more richly detailed account of symbolic systems than is assumed by the authors. Cultural systems are not simply the equivalent in the ideational domain of culture of the purported Baldwin Effect in the genetic domain. © 2014 Cambridge University Press.

Barsalou's theory of perceptual symbol systems is considered from a metacognitive perspective. Two examples are discussed in terms of the proposed perceptual symbol theory. First, recent results in research on feeling-of-knowing judgement are used to argue for a representation of familiarity with input cues. This representation should support implicit memory. Second, the ability of maintaining a theory of other people's beliefs (theory of mind) is considered and it is suggested that a purely simulation-based view is insufficient to explain (...) the available evidence. Both examples characterize areas where Barsalou's theory would benefit from additional detail. (shrink)

A metaphor can often create novel features in an object or a situation. This phenomenon has been particularly hard to account for using amodal symbol systems: although highlighting and downplaying can explain the shift of focus, it cannot explain how entirely new features can come about. We suggest here that the dynamism of perceptual symbol systems, particularly the notion of simulator, provides an elegant account of the creativity of metaphor. The elegance lies in the idea that the creation (...) of new features by a metaphor proceeds in the same way as the creation of regular features in a perceptual symbol. (shrink)

It is very tempting to try to reconcile perception and cognition perceptual symbol systems may be a good way to achieve this; but is there actually a perception-cognition continuum? We offer several arguments for and against the existence of such a continuum and in favor of the choice of perceptual symbol systems. One of these arguments is purely theoretical, some are based on PET-scan observations and others are based on research with handicapped subjects who have communication problems associated (...) with cerebral lesions. These arguments suggest that modal perceptual symbols do indeed exist and that perception and cognition might have a common neuronal basis; but perceptual and cognitive activities require the activation of different neuronal structures. (shrink)