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10963 results in Psychology: general interest

Page 301 of 549

  • 3 - Modularity and cognitive architecture

  • Daniel Weiskopf, Georgia State University, Fred Adams, University of Delaware
  • Book:
    An Introduction to the Philosophy of Psychology
    Published online:
    28 May 2018
    Print publication:
    15 January 2015, pp 64-94

  • Summary

    The mind as a complex system

    Brains and bodies are obvious examples of things – physical entities or objects. Like other paradigmatic physical objects, they have stable spatial boundaries and a host of other properties such as mass, density, and internal composition and organization. But are minds, or the ideas that fill them, also things? Are they object-like in these ways? Cartesian substance dualism, while it denied that the mind was something physical, nevertheless took it to be a kind of object or entity. Descartes argued further that the mind was not only a nonphysical object, but that it was also an indivisible object: it could not be decomposed into parts in any way whatsoever.

    Ontologically, minds are systems, and some systems can also be object-like or entity-like. Atoms, solar systems, biological organisms, and hurricanes are all examples of entity-like systems. As systems they are decomposable into component parts and operations, but like many objects, they are also relatively persistent, coherent, and spatially circumscribed. Given the complex psychological and behavioral phenomena they give rise to, minds must be systems of extreme complexity. Like other complex systems, they have an internal design plan. For artificial computing devices, this plan corresponds to their circuit diagram – the description of their central processors (e.g., their instruction set), memory, system bus, various sub-controllers for storage, networking, audiovisual output, and so on. For biological organisms, this plan corresponds to their overall anatomical organization, their breakdown into organ systems (circulatory system, respiratory system, immune system), into individual organs and other active components (airway, lungs, diaphragm, etc.), and still further into specific types of specialized sub-organs, tissue and cell types, secretions and fluids, and so on.

  • 6 - Perception and action

  • Daniel Weiskopf, Georgia State University, Fred Adams, University of Delaware
  • Book:
    An Introduction to the Philosophy of Psychology
    Published online:
    28 May 2018
    Print publication:
    15 January 2015, pp 155-188

  • Summary

    Defining the senses

    Psychologists have studied perception more deeply than any other of our cognitive capacities, and among the senses vision is by far the most closely scrutinized. Accordingly, although burgeoning philosophical attention has been paid in recent years to nociception (Aydede, 2006), audition (O’Callaghan, 2007), touch (Fulkerson, 2013), and olfaction (Batty, 2011), we mostly confine our attention here to vision. First, however, we address the more general question of how sensory systems are to be distinguished from the rest of cognition, as well as from each other.

    The traditional division that posits five separate senses goes back to Aristotle, at least in recorded Western philosophical thought. Dividing the senses into touch, smell, taste, hearing, and sight makes sense on two intuitive grounds. First, these senses correspond to manifestly different sense organs. The eyes, ears, nose, tongue, and skin are relatively salient parts of the body, and their role in mediating different types of sensory interaction with the environment is pre-scientifically manifest. Second, these sensory divisions seem to be associated with distinct sensory phenomenology. To see something is a different kind of experience than to touch it or hear it. On the basis of anatomy and sensory experience, then, the Aristotelian divisions have some support.

  • 9 - Thought and language

  • Daniel Weiskopf, Georgia State University, Fred Adams, University of Delaware
  • Book:
    An Introduction to the Philosophy of Psychology
    Published online:
    28 May 2018
    Print publication:
    15 January 2015, pp 246-274

  • Summary

    On wordless minds

    Which comes first, thought or language? Do thoughts about the world take shape and then become expressed in a language? Or does one acquire a language first, and only later, or simultaneously by virtue of the very tools of language, gain the ability to think about the world? Descartes notoriously took one of the hardest lines on this question. Speechless animals, he claimed, did not think at all. He may have even meant to imply by this that they lack experience of any kind. The ability to use language in a productive and creative way, for Descartes, was the only sure sign of mentality because it was a performance that could not be duplicated by a mere physical machine. Language is an infinite resource and one that is endlessly adaptable to new contexts. By contrast, the grunts of pigs and the cunning life-and-death dance of wolves hunting sheep are all purely material acts produced by mindless neural machinery.

    To modern ears, this may sound peculiar. Language itself is an evolutionarily recent innovation, one that builds on a complex and extensive foundation of behavioral and cognitive processes. Once we adopt an evolutionary perspective, the phylogeny of cognition appears as a series of increasingly elaborate minds, and the Cartesian attempt to draw a bright line marking out the simultaneous emergence of thought and language seems fruitless (Dennett, 1997).

  • Communication, cognition, and technology

  • Edited by Piotr Łukowski, Aleksander Gemel, Bartosz Żukowski
  • Book:
    Cognition, Meaning and Action
    Published by:
    Jagiellonian University Press
    Published online:
    10 January 2018
    Print publication:
    01 January 2015, pp 109-122

  • Summary

    Introduction

    The most likely form taken by the first human communication was gestures and miming. The body is still an important component in a direct conversation with other people. However, humans are the only animals who have developed a spoken language as our primary tool for communication. Dialogue is our most genuine form of interaction and it will be our point of departure when we compare different forms of communication supported by technology.

    Since early in the history of Homo sapiens, we have used different media for communication. The oldest are cave paintings that are about 40 000 years old. But it is above all written language that has influenced our way of mediating thoughts. The oldest forms of writing are about 5000 years old.

    The last few centuries have seen rapid development of different technologies for communication. Printing was invented a little more than 500 years ago. Telegraphy and photography are about 150 years old. Bell invented the telephone in 1876, Marconi made the first radio transmissions in 1895, Edison taught us how to record sound 100 years ago, and moving pictures are equally old. In the last 50 years we have seen how the fax, the television, the computer and the mobile phone have radically influenced our ways of communicating with other people.

    Imagine, for example that your boyfriend or girlfriend travels to New York to study for a semester. Unfortunately, you are unable to go along. What types of communication technologies will you use to keep your love alive? A handwritten letter is of course very personal, but it will take time before it reaches the addressee. E-mail is an excellent form of communication over long distances for keeping in touch with people; it is fast, cheap and you can write long messages.

    Texting an SMS by mobile phone is not a bad solution but is more suitable for short messages. However, if you want to express your feelings and get an immediate response, the telephone (or the videophone) is the superior medium to “feel close to” the other person. A disadvantage is of course the time difference: you cannot call at any time that suits you.

  • Short- and long-term social interactions from the game theoretical perspective: A cognitive approach

  • Edited by Piotr Łukowski, Aleksander Gemel, Bartosz Żukowski
  • Book:
    Cognition, Meaning and Action
    Published by:
    Jagiellonian University Press
    Published online:
    10 January 2018
    Print publication:
    01 January 2015, pp 181-192

  • Summary

    Introduction

    Game theory is a growing field of analytical modelling of interactions between agents. It has found many applications in economics and business administration, as well as in social and cognitive sciences. Among various forms of one-off and multi-period games, the probably most popular one is known as a prisoner's dilemma. This paper analyses the social interactions from the perspective of the equilibria resulting from the prisoner's dilemma models with a short and indefinite time horizon.

    A one-period interaction modelled in the prisoner's dilemma setting results in an equilibrium point where the agents are maximising their short-term profit and thus, interacting, they reach a suboptimal point of overall welfare. However, in a model with an indefinite time framework, it is likely to reach an equilibrium which is consistent with the cooperative behaviour over a longer period of time. In result, an optimal point from the perspective of welfare is reached. In the following analysis, we relate these model results to social interactions and discuss their possible applications in cognitive science.

    The paper is related to the literature on game theory and its applications in social interactions. Research in game theory dates back to the nineteenth century, when, among others, the theories of strategic interaction in oligopolies have been developed (see, e.g. Bertrand, 1883, or Varian, 2006 for an overview). In the first half of the 20th century, Neumann and Morgenstern (1944) applied game theory to the economic interactions among agents who maximise their utility (see also Neumann, 1928 or Copeland, 1945 for the review of Neumann, Morgenstern, 1944). Following this, the field grew intensively, with the range of underlying concepts developed and extensive applications to many areas of economic research (see, e.g. Shapiro, 1989; Kreps, 1990 and Selten, 1999). In particular, in 1994 John C. Harsanyi, John F. Nash Jr. and Reinhard Selten received the Nobel Prize in Economic Sciences “for their pioneering analysis of equilibria in the theory of non-cooperative games”. Following this work, game theoretical results have been validated from the behavioural perspective, as well as by experiments (see, e.g. Smith, 1992 or Crawford, 1997),2 while the framework to analyse conflict and cooperation of economic agents has been developed further.

  • To tell and to show: The interplay of language and visualizations in communication

  • Edited by Piotr Łukowski, Aleksander Gemel, Bartosz Żukowski
  • Book:
    Cognition, Meaning and Action
    Published by:
    Jagiellonian University Press
    Published online:
    10 January 2018
    Print publication:
    01 January 2015, pp 123-136

  • Summary

    The use of imitation, gestures and pictures has played a very important role in the evolution of human cognition (Zlatev et al., 2005; Persson, 2008). Another important strand of research has studied the human ability to communicate multimodally, by using a combination of language, mimics, gestures, pictures, and body movements (Allwood, 2002).

    Let us have a closer look at the use of various types of visualization that accompany language in communication. Imagine a group of friends involved in a lively conversation about their holiday adventures. Whether they talk about a dangerous bungy-jumping experience, hiking in the mountains, or enjoying the beach and pub life, they behave in a similar way. They do not only use language to describe events and things; they also use gestures, draw sketches, imitate voices, and engage their whole body to re-enact events. In short, when narrating, they not only tell but also show their experiences, tales, or stories.

    Since Plato and Aristotle, these two activities are called diegesis (narrators describe things) and mimesis (narrators show things). In the following, we will be concerned with mimesis in more detail, following the distinctions made by Clark (2004). The term mimesis has been taken by Plato from music theory and applied to designate scenic performance where actions of persons are imitated and re-enacted. In other words, mimesis is a re-production based on imitation of an action. In communication, mimesis is important for both speakers and listeners. It is a means of showing actions to make them visible (and audible) to the listeners. By using voice, gestures, and drawings, the speakers create scenes, embody and dramatize events, and thereby involve their partners. “Mimesis gives us the sense of reality in fiction, the illusion of access to the reality of personal experience” (Lodge, 1990: 144). The more effective the imagination, the better the possibility for the audience to visualize the speaker's experience.

    There is, however, an important distinction to be made between two ways of “showing”: on the one hand we can indicate something by pointing at an object, on the other hand we can demonstrate things with the help of our voice, hands, or body.

  • Cognitive science: From computers to ant hills as models of human thought

  • Edited by Piotr Łukowski, Aleksander Gemel, Bartosz Żukowski
  • Book:
    Cognition, Meaning and Action
    Published by:
    Jagiellonian University Press
    Published online:
    10 January 2018
    Print publication:
    01 January 2015, pp 11-30

  • Summary

    Before cognitive science

    In this introductory chapter some of the main themes of the development of cognitive science will be presented. The roots of cognitive science go as far back as those of philosophy. One way of defining cognitive science is to say that it is just naturalized philosophy. Much of contemporary thinking about the mind derives from René Descartes’ distinction between the body and the soul. They were constituted of two different substances and it was only humans that had a soul and were capable of thinking. According to him, other animals were mere automata.

    Descartes was a rationalist: our minds could gain knowledge about the world by rational thinking. This epistemological position was challenged by the empiricists, notably John Locke and David Hume. They claimed that the only reliable source of knowledge is sensory experience. Such experiences result in ideas, and thinking consists of connecting ideas in various ways.

    Immanuel Kant strove to synthesize the rationalist and the empiricist positions. Our minds always deal with our inner experiences and not with the external world. He introduced a distinction between the thing in itself (das Ding an sich) and the thing perceived by us (das Ding an uns). Kant then formulated a set of categories of thought, without which we cannot organize our phenomenal world. For example, we must interpret what happens in the world in terms of cause and effect.

    The favourite method among philosophers of gaining insights into the nature of the mind was introspection. This method was also used by psychologists at the end of the 19th and the beginning of the 20th century. In particular, this was the methodology used by Wilhelm Wundt and other German psychologists. By looking inward and reporting inner experiences it was hoped that the structure of the conscious mind would be unveiled.

    However, the inherent subjectivity of introspection led to severe methodological problems. These problems set the stage for a scientific revolution in psychology. In 1913, John Watson published an article with the title “Psychology as the behaviourist views it” which has been seen as a behaviourist manifesto. The central methodological tenet of behaviourism is that only objectively verifiable observations should be allowed as data.

  • Two procedures expanding a linguistic competence

  • Edited by Piotr Łukowski, Aleksander Gemel, Bartosz Żukowski
  • Book:
    Cognition, Meaning and Action
    Published by:
    Jagiellonian University Press
    Published online:
    10 January 2018
    Print publication:
    01 January 2015, pp 31-50

  • Summary

    Introduction

    On the ground of psychology there are many various theories explaining what a notion is. All these approaches can be grouped in three classes:

  • (A) classical theories which present a notion as a compilation of features in common for many particular objects.

  • (B) probabilistic theories in which notions are derived from the higher structure

  • – an individual theory of the world. Notions are elements of the structure.

  • (C) theories in which a notion is strictly connected with its references and with other notions.

    • Theories of the first class are a little bit naïve today, and theories of the second class fail because of the error of circularity – in order to explain what a notion is, we need to explain what a structure is, but in order to explain what a structure is, we need to know what a notion is (Maruszewski, 2001: 297–299). Theses of theories of the third class are obviously compatible with simple everyday observations and with the logical knowledge about the properties of natural language expressions. Thus, the approach presented in the paper coincides with the main ideas of the theories of this last class.

    Dialogue 1

  • During a stroll with his father a boy asks: – What is it, daddy?

  • – A building, honey – the father answers.

  • – Oh…

  • – And this is another building, isn't it? – after a while the child adds pointing at next object.

  • – No, it isn't. This is a shed.

  • – Why this is not a building? – the boy asks.

  • – Because it is much smaller than a building, it is constructed from ordinary boards, it is not for living, just for garden's tools…

  • – Uh-huh…

    • Dialogue 2

  • During a stroll with his father a child asks: – What color is this leaf?

  • – It is brown – the father answers.

  • – It's impossible! Your jacket is brown and the leaf's color is different.

  • – My jacket is brown and the leaf is also brown. Both colors are a little bit different but both are brown – the father states.

  • – And what about that car's color? – the boy asks.

  • – I'm afraid the car is not brown – the father answers – that car's color has a delicate red shade.

  • The crossroads of cognitive science

  • Edited by Piotr Łukowski, Aleksander Gemel, Bartosz Żukowski
  • Book:
    Cognition, Meaning and Action
    Published by:
    Jagiellonian University Press
    Published online:
    10 January 2018
    Print publication:
    01 January 2015, pp 7-10

  • Summary

    The monograph Cognition, Meaning and Action. Lodz-Lund Studies in Cognitive Science collects papers written by the members of two Cognitive Science Departments: of Lund and of Lodz. It presents a range of issues currently examined in both centers. Some texts are written in collaboration as the result of collective research.

    The opening article “Cognitive science: From computers to ant hills as models of human thought” (Peter Gärdenfors) offers an introduction to the history of ideas in cognitive science as it has been developing throughout last decades. Much of the contemporary mind theories derive from Descartes’ res cogitans and res extensa distinction, and to some extent they may be seen as a continuation of rationalist-empiricist debate. The dawn of computer science is kept in quite rationalist fashion. The fundamental concept of computer science is the theoretical construct of Turing's machine. Inspired by Turing's concept, John von Neumann proposes a general architecture for modern computer based on logic circuits. The transfer of these findings to a theory of how the mind works was only a matter of time. Soon after von Neumann's proposal, McCulloch and Pitts interpreted neurons as a logic circuits combining information from other neurons according to some logical operations. This leads directly to one conclusion: the entire brain is a huge computer – and so the foundational metaphor for cognitive science was born.

    Cognitive science can be said to emerge in 1956, the year in which Noam Chomsky, in response to the behaviourist concept of language, presented his proposition of transformational grammar. His central argument is based on the claim that processing the grammar of natural language requires a sort of algorithm as used in Turing machine. Also in 1956 Newell and Simon demonstrated the first computer program constructing logical proofs from a given set of premises and, finally, the concept of Artificial Intelligence was used for the first time. The philosophical assumption of the AI approach to cognitive processes is that the representation of mental content and processing is essentially symbol manipulation: only logical relations connect different symbolic expressions in a mental state of a person. The meaning of symbols is not part of the process of thinking, since they are manipulated exclusively on the basis of their form.

  • Semiotics, signaling games and meaning

  • Edited by Piotr Łukowski, Aleksander Gemel, Bartosz Żukowski
  • Book:
    Cognition, Meaning and Action
    Published by:
    Jagiellonian University Press
    Published online:
    10 January 2018
    Print publication:
    01 January 2015, pp 137-152

  • Summary

    Introduction

    The 20th-century discussion on meaning was dominated by two distinct schools of thought – by that of naturalistic semantics and by that of structural semiotics. Although the two have traditionally been viewed as conflicting approaches, the main aim of this paper is to show that they can be seen as complementary to one another. In order to achieve this objective, we will examine the advantages and drawbacks of both approaches (represented, respectively, by Eco's semiotics and Skyrms’ game-theoretical semantics). The results obtained this way provide a basis for further development of hybrid system by combining features of structural and naturalistic models.

    Structural semiotics. Between signalization and signification

    The distinctive feature of structural semiotics is a strict separation of two independent semiotic systems: signalization and signification. At the same time, in accordance with the basic premise of structural semiotics, it is only through both of these autonomic systems that a proper communication process can work successfully. Considered in itself, signalization is simply “the passage of a signal (not necessarily a sign) from a source (through a transmitter, along a channel) to a destination” (Eco, 1976: 8). The signals used for this process derive from a special kind of semiotic system called s-code, resulting from the division of some natural or artificial continuum. An essential feature of s-code is that all of the primary system components are isolated arbitrarily (ibid.: 77). Nevertheless, when selected, they are to form a well-organized, independent system, in which the identity of each unit is completely determined by reference to others, and hence specified by its position in the whole (ibid.: 38). The system established in this way is an internally structured matrix with certain combinatorial properties (determined by a set of combinatorial rules). As a result, it possesses also some informational potential. It is precisely (mathematically) defined by the intrinsic properties of the system (arrangement of elements and combinatorial rules), determining the amount of information possible to transmit. So configured, the system can operate autonomously – without any semantic reference: “s-codes are systems or ‘structures’ that can also subsist independently of any sort of significant or communicative purpose” (ibid.).

  • Neurobiological basis for emergence of notions

  • Edited by Piotr Łukowski, Aleksander Gemel, Bartosz Żukowski
  • Book:
    Cognition, Meaning and Action
    Published by:
    Jagiellonian University Press
    Published online:
    10 January 2018
    Print publication:
    01 January 2015, pp 51-62

  • Summary

    Introduction

    Even though psychology and logic share several topics of common interest, they operate within different paradigms and therefore encounter difficulties in mutual communication of their advances. One of the most dire problems shared by both is the question of acquisition and structure of notions. Both of these issues have been minutely addressed from perspective of logic in the previous article entitled “Two procedures expanding a linguistic competence” (Łukowski, 2015). The theory proposed there for development of linguistic competence and ontogenesis of notions, has significant impact on foundations of semantics. Its claims could not be made if not for several neuroscientific insights into functioning of the central nervous system that resulted in refining the models of cognitive processes. It is apparent that emergence of notions in an individual is a direct product of brain activity. Even though philosophers still contest the character of relationship between neural function and psychological phenomena, it is no longer controversial in science that the structure of the first determines the structure of the latter. Following that, any theory expressed in language of psychology or philosophy should comply with inferences concerning the architecture of thinking that is derived from neurophysiological data. Although there is a vast amount of information concerning neurobiological correlates of psychological phenomena some of them are of special interest in the discourse on notions and the meaning of words. This chapter will focus especially on biological substructure underlying vagueness, generality, dynamicity and temporality of notions.

    Basic concepts

    Every neuronal network, be it artificial or natural, requires constant flow of new inputs (information) to properly function and produce useful output. In case of the human brain inputs are provided by receptors of sensory systems. Contrary to the popular belief, humans have more than five senses. Their actual number is estimated to be around twenty, depending on adopted definition of sense. When matter of learning is raised, it is customary in philosophy to concentrate the argument around visual perception. That practice is not groundless as majority of sensory information received by human brain is visual. 10 bits of information is coded by retina each second. Considering that human cortical, sensory network is approximately convergent (Foxe, Schroeder, 2005), only a fraction of the mentioned amount of information reaches cerebral cortex. Around 104 bits/sec ultimately reaches the fourth layer of primary visual cortex (V1) (Raichle, 2010).

Cognition, Meaning and Action
  • Lodz-Lund Studies in Cognitive Science
  • Edited by Piotr Łukowski, Aleksander Gemel, Bartosz Żukowski
  • Published by:
    Jagiellonian University Press
    Published online:
    10 January 2018
    Print publication:
    01 January 2015
  • The book is addressed to all readers interested in cognitive science, and especially in research combining a logical analysis with psychological, linguistic and neurobiological approaches. The publication is the result of a collaboration between the Department of Cognitive Science at University of Lodz and the Department of Cognitive Science at Lund University. It is intended to provide a comprehensive presentation of the key research issues undertaken in both Departments, including considerations on meaning, natural language and reasoning, linguistic as well as numerical competence, the theory of decision making, modelling of conceptual representations, cognitive and game theoretic approach to social interactions.
    Jacek Malinowski

  • Out of the box thinking

  • Edited by Piotr Łukowski, Aleksander Gemel, Bartosz Żukowski
  • Book:
    Cognition, Meaning and Action
    Published by:
    Jagiellonian University Press
    Published online:
    10 January 2018
    Print publication:
    01 January 2015, pp 153-168

  • Summary

    Introduction

    If we accept that out of the box thinking is important, especially when hitherto existing solutions are applied to little avail, then understanding this process is also extremely important.

    The primary observation here is that out of the box thinking is powerfully constrained by the very nature. In addressing this phenomenon we need to recognize that once the mind is furnished, it is difficult for it to entertain novelty. Viewing the situation through the metaphor of canyon and plain not only allows for an insight into this question but also offers a method of inducing a change.

    Canyon

    Fancy that you are moving along some deep canyon and all you can see are its walls of stone. You feel safe inside and just follow the unique direction possible.

    As much evidence shows, some part of human thinking may be compared to torrents flowing in deep canyons. And as in a real ravine the visual perspective is confined by its slopes and one can follow the only path, similarly, the train of thoughts is limited to the most easily accessible and immediate “pathways” without perceiving the possibility of choice or change. These are real thinking canyons, i.e. most deeply rooted and long-standing beliefs, attitudes, and opinions. They are the last to be changed. They play the role of a censor sometimes causing a cognitive dissonance, for example, a person who is asked to write an article defending views contrary to their own and paid a negligible amount of money experiences cognitive dissonance and to avoid it starts to agree with what he/she has written. Thus, their prevailing canyon: I am rational, remains unaltered. Even Einstein succumbed to the canyons (he was convinced that the universe cannot change) and added a cosmological constant to stop the expansion (or contraction) predicted by his own relativity theory.

    The question about the source of such canyons has at least two complementary answers.

    First, this feature of thinking seems to be strictly connected with the traits of our memory, but not, which should be emphasized, with any memory impairment.

  • The Approximate Numbers System and the treatment of vagueness in conceptual spaces

  • Edited by Piotr Łukowski, Aleksander Gemel, Bartosz Żukowski
  • Book:
    Cognition, Meaning and Action
    Published by:
    Jagiellonian University Press
    Published online:
    10 January 2018
    Print publication:
    01 January 2015, pp 87-108

  • Summary

    Introduction

    The theory of conceptual spaces is intended to provide a framework for models of both symbolic and non-symbolic representations of knowledge and information (Gärdenfors 2000). As such, it seems to us to be very clearly suited to modeling pre-verbal representations belonging to a so-called core cognition, whose existence is postulated by cognitive developmental psychologists (Feigenson et al., 2004; Carey, 2009). In this paper we propose a treatment of representations of quantity that embraces both symbol-based and pre-verbal numerical concepts.

    The representations we aim to study are related to the Approximate Number System (ANS). Cognitive psychologists claim that humans share with animals an abstract sense of quantity: they have a so-called “number sense”. To “number sense” amounts two core systems of representations, which get activated by different core mechanisms: the ANS is one of these mechanisms (Dehaene 1997, 2008; Gallistel 1993; Feigenson et al., 2004; Carey, Sarnecka, 2006).

    The ANS is a core system in the sense that it is present in human apprehension of quantities before verbal conceptual these of quantities appears. But, it is claimed, it also underlies symbolic number-concept creation and it is active in the processing of quantitative information for the entire life of an individual. Firstly it reacts to nonverbal input and this remains the case through the whole lifespan (Halberda, Feigenson, 2008), it also gets activated through symbolic input. To exemplify the functioning of the ANS and the ANS-related representations, let us consider the following case: the reaction to a set of 17 elements corresponds to the seventeenth element of the ANS-sequence, i.e. a set containing 17 with some specific neighboring area.

    It is not our objective to postulate anything about the relation between exact number names, i.e. numerals, and representations related to the ANS (Halberda, Feigneson, 2008; Mussolin et al., 2012; Wagner, Johnson, 2011; see also Nagen, Sarnecka, 2015). Instead, we observe that numerals are in certain contexts interpreted as vague terms (Krifka, 2009; Solt, 2011). It might seem surprising, as at first glance there is nothing less vague than a number. “Seven” refers to seven; “twelve dwarfs” are twelve entities of the type“dwarf”, etc.

  • Similarity as distance: Three models for scientific conceptual knowledge

  • Edited by Piotr Łukowski, Aleksander Gemel, Bartosz Żukowski
  • Book:
    Cognition, Meaning and Action
    Published by:
    Jagiellonian University Press
    Published online:
    10 January 2018
    Print publication:
    01 January 2015, pp 63-86

  • Summary

    Introduction

    Starting with Minsky (1975) and more widely recognized since Barsalou (1992), (dynamic) frames have become a well-accepted tool to model conceptual knowledge. We begin our comparison with its predecessor model, the feature list, and trace its development into the (dynamic) frame model. Subsequently, we summarize extant frame-style reconstructions of taxonomic change as a paradigmatic application within history and philosophy of science, thus addressing the incommensurability of frameworks, or world-views, from a cognitive historical perspective.

    We hold that a frame is a sophisticated feature list whose application centrally supports the claim that historically successive taxonomies are comparable. But we criticize that the frame model yields little insight beyond taxonomic change. Introducing conceptual spaces as an alternative model, we discuss dimensions, their combinations, how to recover frames by analogue expressions, similarity as geometric distance across diachronically varying spaces, and the status of scientific laws.

    Feature lists, frames, spaces

    Originating in Aristotelian philosophy (Taylor, 2003), the feature list constitutes both an entrenched and a somewhat outdated tool for reconstructing conceptual knowledge. Paradigmatically instantiated by taxonomic knowledge, e.g., in biology, it can be summarized by three assumptions: (i) the representation of a concept provides a summary of the class of its instances (i.e., the things falling under the concept); (ii) the binary features representing a concept are individually necessary and jointly sufficient to define the concept; (iii) features are nested in subset relations such that, if concept X is a subset of concept Y, then the defining features of Y are nested in those of X. Such features are regularly referred to as defining or essential (see Kuukkanen, 2006: 88).

    On the classical view, combinations of binary features (aka attributes) provide a definition of that which falls under, or instantiates, a concept if and only if the features are present in, or true of, the thing. Features are normally rendered in natural language, typically by nouns or adjectives. The classical example sees MAN being analyzed as [+biped, +rational, +animal]. Standardly, problems arise upon observing, for instance, that a Para-Olympic athlete may thus fail to instantiate MAN – which is somewhat absurd. Short of allowing ad hoc modifications, or throwing individually necessary and jointly sufficient features over board, however, the absurdity is not easily remedied.

Page 301 of 549