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)

How should a practice, subservient to a public good, be regulated in order to guarantee fair access without encouraging improper claims? In the first place, a clear understanding of the goal of the practice is indispensable for knowing what criteria the regulation must contain. As to the purely formal aspect, the regulation of any practice must include both general rules and particular instances. Finally, to resolve conflicts, committees in which different kinds of expertise are represented should be installed. These three (...) theses are illustrated by the Dutch regulation for cosmetic surgery. (shrink)

Traditionally, theories of concepts in psychology assume that concepts are a single, uniform kind of mental representation. But no single kind of representation can explain all of the empirical data for which concepts are responsible. I argue that the assumption that concepts are uniformly the same kind of mental structure is responsible for these theories’ shortcomings, and outline a pluralist theory of concepts that rejects this assumption. On pluralism, concepts should be thought of as being constituted by multiple representational kinds, (...) with the particular kind of concept used on an occasion being determined by the context. I argue that endorsing pluralism does not lead to eliminativism about concepts as an object of scientific interest. (shrink)

Conceptual atomists argue that most of our concepts are primitive. I take up three arguments that have been thought to support atomism and show that they are inconclusive. The evidence that allegedly backs atomism is equally compatible with a localist position on which concepts are structured representations with complex semantic content. I lay out such a localist position and argue that the appropriate position for a non-atomist to adopt is a pluralist view of conceptual structure. I show several ways in (...) which conceptual pluralism provides an advantage in satisfying the empirical and philosophical demands on a theory of conceptual structure and content. (shrink)

Though predictive processing approaches to the mind were originally applied to exteroceptive perception, i.e., vision and action, recent work has started to explore the role of interoceptive perception, i.e., emotion and affect. This article builds on this work by extending PP beyond emotion to the construction of emotional dispositions. I employ principles from dynamical systems theory and PP to provide a model of how dispositional anger can develop in response to early experiences of psychosocial stress. The model is then deployed (...) to explain the established link between psychosocial stress in early life and the appearance of certain organic disease phenotypes in later life. This phenomenon can appear mysterious when viewed through the standard biomedical explanatory lens, which has difficulty accounting for the causal influence of subjective perceptions and evaluations of the social and material environment on the development of organic disease processes. The model provided presents such cases as instances of developmental mismatch. They occur when an organism develops an emotional disposition that leads them to make habitually-biased appraisals of what the social environment affords. The model provides a novel explanation of certain organic disease phenotypes with top-down and developmental causes, and demystifies one class of cases involving apparently spooky ‘mind-to-matter’ causation. (shrink)

The traditional definition per genus et differentiam is argued to be cognitively grounded in perception and in order to avoid needless argument, definitions are stipulated to assert boundaries. An analysis of the notion of perspective shows that a boundary is a composite of two distinctions: similarity that includes and difference that excludes. The concept is applied to the type-token distinction and percepts are shown to be the result of a comparison between a token as representing some phenomenon and a type (...) as representing the kind of object the phenomenon might be. The Principle of Connection is proposed as the mental architecture that gives rise to percepts. The value of a percept is shown to be one of Identical, Similar, Different or Contrary and its perceptual aspects represent the cognitive schema of Essence, Quality, Quantity and Relation. The two notions of similarity and difference are claimed to constitute the necessary and sufficient conditions for definitions. Accordingly, the qualitative elements of a definition signify the genus as representing the similarity of the defined entity in terms of others of its kind and the quantitative elements signify the differentia as representing the difference it has from everything else. Paying proper attention to both qualitative and quantitative aspects will enable formulation of definitions that are ‘good’. (shrink)

In this paper, we examine a specific type of Relative Clause. We look at the construction consisting of a ‘light noun’, that is, a noun with highly non-specific lexical content which does not do referential work, plus a relative clause. It has generally been assumed that the functional contribution of RCs is to narrow the set of referents of the head noun to only those for which the predicate of the RC holds true. However, the ‘Light Head RC construction’ has (...) various interactional affordances that mostly revolve around characterizing referents with discourse-relevant properties rather than establishing reference. We argue that these various functions of LHRCs revolve around participants’ orientations to categoryhood. Data are in English and Dutch. (shrink)

We argue that are no such things as literal categories in human cognition. Instead, we argue that there are merely temporary coalescences of dimensions of similarity, which are brought together by context in order to create the similarity structure in mental representations appropriate for the task at hand. Fodor contends that context‐sensitive cognition cannot be realised by current computational theories of mind. We address this challenge by describing a simple computational implementation that exhibits internal knowledge representations whose similarity structure alters (...) fluidly depending on context. We explicate the processing properties that support this function and illustrate with two more complex models, one applied to the development of semantic knowledge , the second to the processing of simple metaphorical comparisons . The models firstly demonstrate how phenomena that seem problematic for literal categorisation resolve to particular cases of the contextual modulation of mental representations; and secondly prompt a new perspective on the relation between language and thought: language affords the strategic control of context on semantic knowledge, allowing information to be brought to bear in a given situation that might otherwise not be available to influence processing. This may explain one way in which human thought is creative, and distinctive from animal cognition. (shrink)

Emotion Review, Volume 14, Issue 2, Page 116-120, April 2022. To make progress related to long-standing questions related to the nature of emotion, we offer the Interactive Activation and Competition framework for Emotion. The IAC-E is not another conventional theory of emotion. Rather, it offers a neural-network-based, algorithmic account of how emotion instances and categories arise. Our approach suggests that there need not be a contradiction between instances of the same emotion being sometimes consistent and sometimes variable. Similarly, there need (...) not be a contradiction between observations of homogeneity and heterogeneity within emotion categories. (shrink)

This article addresses issues in developing cognitive architectures--generic computational models of cognition. Cognitive architectures are believed to be essential in advancing understanding of the mind, and therefore, developing cognitive architectures is an extremely important enterprise in cognitive science. The article proposes a set of essential desiderata for developing cognitive architectures. It then moves on to discuss in detail some of these desiderata and their associated concepts and ideas relevant to developing better cognitive architectures. It argues for the importance of taking (...) into full consideration these desiderata in developing future architectures that are more cognitively and ecologically realistic. A brief and preliminary evaluation of existing cognitive architectures is attempted on the basis of these ideas. (shrink)

Conceptual spaces are a frequently applied framework for representing concepts. One of its central aims is to find criteria for what makes a concept natural. A prominent demand is that natural concepts cover convex regions in conceptual spaces. The first aim of this paper is to analyse the convexity thesis and the arguments that have been advanced in its favour or against it. Based on this, I argue that most supporting arguments focus on single-domain concepts (e.g., colours, smells, shapes). Unfortunately, (...) these concepts are not the primary examples of natural concepts. Building on this observation, the second aim of the paper is to develop criteria for natural multi-domain concepts. The representation of such concepts has two main aspects: features that are associated with the concept and the probabilistic correlation pattern which the concept captures. Conceptual spaces, together with probabilistic considerations, provide a helpful framework to approach these aspects. With respect to feature representation, the existence of characteristic features (i.e., that apples have a specific taste) is essential. Moreover, natural concepts capture peaks of a probabilistic distribution over complex spaces. They carve up nature at its joints, that is, at areas with no or low probabilistic density. This last aspect is shown to be closely related to the convexity demand. (shrink)

This paper addresses two issues: what it is for a metaphor to be either alive or dead and what a metaphor must be in order to be either alive or dead. Both issues, in turn, bear on the contemporary debate whether metaphor is a pragmatic or semantic phenomenon and on the dispute between Contextualists and Literalists. In the first part of the paper, I survey examples of what I take to be live metaphors and dead metaphors in order to establish (...) that there is a phenomenon here to be explained. I then propose an explanation of metaphorical vitality in terms of the dependence of the interpretation of a metaphor on a family or network of expressions specific to its context of utterance. I then argue that only a Literalist account of metaphor — one that posits metaphorical expressions )—and not Contextualist and Gricean approaches can accommodate this explanation. Finally, I discuss some objections to my Literalist account and sketch an explanation of types to counter Platonistic objections to my metaphorical expression types. (shrink)

Schober et al. describe two studies on how survey interview respondents misunderstand interview questions. After answering a survey, participants are given standardized definitions of the questions they have just answered. Even apparently simple questions such as “Have you smoked more than 100 cigarettes?” are interpreted very differently by participants. Moreover, clarifying the meaning of the definitions with the interviewer does not always help resolve the miscommunication.

The inductive category formation framework, an influential set of theories of learning in psychology and artificial intelligence, is deeply flawed. In this framework a set of necessary and sufficient features is taken to define a category. Such definitions are not functionally justified, are not used by people, and are not inducible by a learning system. Inductive theories depend on having access to all and only relevant features, which is not only impossible but begs a key question in learning. The crucial (...) roles of other cognitive processes (such as explanation and credit assignment) are ignored or oversimplified. Learning necessarily involves pragmatic considerations that can only be handled by complex cognitive processes.We provide an alternative framework for learning according to which category definitions must be based on category function. The learning system invokes other cognitive processes to accomplish difficult tasks, makes inferences, analyses and decides among potential features, and specifies how and when categories are to be generated and modified. We also examine the methodological underpinnings of the two approaches and compare their motivations. (shrink)

Previous neural network models of concept learning were mainly implemented with supervised learning schemes. However, studies of human conceptual memory have shown that concepts may be learned without a teacher who provides the category name to associate with exemplars. A modular neural network architecture that realizes concept acquisition through two functionally distinct operations, categorizing and naming, is proposed as an alternative. An unsupervised algorithm realizes the categorizing module by constructing representations of categories compatible with prototype theory. The naming module associates (...) category names to the output of the categorizing module in a supervised mode. In such a modular architecture, the interface between the modules can be conceived of as an “information relay” that encodes, constrains, and propagates important information. Five experiments were conducted to analyze the relationships among internal conceptual codes and simple conceptual and lexical development. The first two experiments show a prototype effect and illustrate some basic characteristics of the system. The third experiment presents a bottom‐up model of the narrowing down of children's early lexical categories that honors mutual exclusivity. The fourth experiment introduces top‐down constraints on conceptual coding. The fifth experiment exhibits how hierarchical relationships between concepts are learned by the architecture, and also demonstrates how a spectrum of conceptual expertise may gradually emerge as a consequence of experiencing more with certain categories than with others. (shrink)

In their exhaustive study of the cognitive operation of analogy, Hofstadter and Sander arrive at a paradox: the creative and inexhaustible production of analogies in our thought must derive from a “reminding” operation based upon the availability of the detailed totality of our experience. Yet the authors see no way that our experience can be stored in the brain in such detail nor do they see how such detail could be accessed or retrieved such that the innumerable analogical remindings we (...) experience can occur. Analogy creation, then, should not be possible. The intent here is to sharpen and deepen our understanding of the paradox, emphasizing its criticality. It will be shown that the retrieval problem has its origins in the failure of memory theory to recognize the actual dynamic structure of events. This structure is comprised of invariance laws as per J. J. Gibson, and this event “invariance structure” is exactly what supports Hofstadter and Sander’s missing mechanism for analogical reminding. Yet these structures of invariants, existing only over optical flows, auditory flows, haptic flows, etc., are equally difficult to imagine being stored in a static memory, and thus only exacerbate the problem of the storage of experience in the brain. A possible route to the solution of this dilemma, based in the radical model of Bergson, is also sketched. (shrink)

A common presupposition in the concepts literature is that concepts constitute a sin- gular natural kind. If, on the contrary, concepts split into more than one kind, this literature needs to be recast in terms of other kinds of mental representation. We offer two new arguments that concepts, in fact, divide into different kinds: (a) concepts split because different kinds of mental representation, processed independently, must be posited to explain different sets of relevant phenomena; (b) concepts split because different kinds (...) of mental representation, processed independently, must be posited to explain responses to different kinds of category. Whether these arguments are sound remains an open empirical question, to be resolved by future empirical and theoretical work. (shrink)

Abstract How do people find arguments while engaged in a discussion? Following an analogy with visual search, a mechanism that performs this task is described. It is a metarepresentational device that examines representations in a mostly serial manner until it finds a good enough argument supporting one’s position. It is argued that the mechanism described in dual process theories as ‘system 2’, or analytic reasoning fulfills these requirements. This provides support for the hypothesis that reasoning serves an argumentative function. Content (...) Type Journal Article Pages 1-20 DOI 10.1007/s10503-011-9256-1 Authors Hugo Mercier, Philosophy, Politics and Economics Program, University of Pennsylvania, 313 Cohen Hall, 249 South 36th Street, Philadelphia, PA 19104, USA Journal Argumentation Online ISSN 1572-8374 Print ISSN 0920-427X. (shrink)

McRae, Brown and Elman argue against the view that events are structured as frequently‐occurring sequences of world stimuli. They underline the importance of temporal structure defining event types and advance a more complex temporal structure, which allows for some variance in the component elements.

How do we construct ad hoc concepts, especially those characterised by emergent properties? A reasonable hypothesis, suggested both in psychology and in pragmatics , is that some sort of inferential processing must be involved. I argue that this inferential processing can be accounted for in associative terms. My argument is based on the notion of inference as associative pattern completion based on schemata, with schemata being conceived in turn as patterns of concepts and their relationships. The possible role of conscious (...) attention in inferential processes of this sort is also addressed. (shrink)

We propose that the pragmatic factors that mediate everyday deduction, such as alternative and disabling conditions (e.g. Cummins et al., 1991) and additional requirements (Byrne, 1989) exert their effects on specific inferences because of their perceived relevance to more general principles, which we term SuperPs. Support for this proposal was found first in two causal inference experiments, in which it was shown that specific inferences were mediated by factors that are relevant to a more general principle, while the same inferences (...) were unaffected by factors not relevant to the general principle. These results were extended to deontic inferences in two further experiments. Taken together, these findings show that unstated superordinate principles play a significant role in certain types of reasoning. Questions raised by the findings for the main theoretical approaches are discussed. (shrink)

Measuring perceived similarity is an important issue in visual perception of faces, since a measure of the perceived similarity between faces may be used to investigate fundamental tasks like face categorization and recognition. Despite its fundamental role, measuring perceived similarity between faces is not trivial from both a theoretical and methodological point of view. In this paper we present theoretical arguments that undermine the method currently most used to measure perceived similarity between faces in visual perception, and we propose an (...) alternative method. We finally compare the two methods and find some empirical evidence that the proposed method can provide a more reliable evaluation of the perceived similarity between faces. (shrink)

In this article we take the use of examples as a means to explore the processes of persuasion and consensus-construction involved in the legitimation of popular management knowledge. Examples, as concrete instances or events used to substantiate a wider argument, have been variedly regarded in different research traditions. Classical logic and rhetoric have considered them an inferior form of argument, useful for pedagogic or public debate but inadequate for higher forms of thought. This spirit still permeates much psychological research on (...) communication, where the great persuasive import of examples has been contrasted with more scientific and formal resources for argumentation. Considered in this light, the contingent and episodic nature of examples seems to make them cognitively inferior to explicit statements of general rules. However, various strands of research on the nature of scientific knowledge have shown that implicit forms of knowledge are an integral part of scientific expertise. Examples may thus be more central to disciplinary thought than the conventional normative view seems to allow. In this spirit, we explore the use of examples in a hotly contested field, that of popular discourse on business and management. The profusion of examples in this kind of writing has been often noted, and almost as often criticized. We seek to explore more fully how these examples are deployed, examining the discursive devices that mark examples within the development of the text, their function as rhetorical moves, and their role in presenting arguments that are never otherwise made explicit. (shrink)

This paper reports a case study on a family of American English constructions that will be called the family of approximate comparison constructions. This family has three members, all of which follow the syntactic pattern about as X as Y with X being an adjective, but which allow three related functions: literal comparison, simile and irony. Two cognitive frameworks concern themselves with irony, the cognitive modelling approach and viewpoint approach, and the paper will show that, while the ironic approximate comparison (...) construction calls central assumptions of the cognitive modelling approach to question, the viewpoint account can be refined to handle these cases. In doing so, it furthers our understanding of the cognitive underpinning of irony. The paper provides a corpus-based analysis on the Y slot as well as collostructional analyses on the adjectival X slot in the family of approximate comparison constructions. The results thereof suggest that the ironic approximate comparison construction, in comparison to its literal counterpart, prefers adjectives that convey positively connotated, nuanced attitudes and is formally less variable in the Y slot. The preference for particular adjectives lends further support to the assumption that hearers understand the construction as ironic or literal before speakers complete their utterance. Given that, it is argued that the ironic approximate comparison construction communicates an inherent viewpoint. (shrink)

Recent progress in artificial intelligence has renewed interest in building systems that learn and think like people. Many advances have come from using deep neural networks trained end-to-end in tasks such as object recognition, video games, and board games, achieving performance that equals or even beats that of humans in some respects. Despite their biological inspiration and performance achievements, these systems differ from human intelligence in crucial ways. We review progress in cognitive science suggesting that truly human-like learning and thinking (...) machines will have to reach beyond current engineering trends in both what they learn and how they learn it. Specifically, we argue that these machines should build causal models of the world that support explanation and understanding, rather than merely solving pattern recognition problems; ground learning in intuitive theories of physics and psychology to support and enrich the knowledge that is learned; and harness compositionality and learning-to-learn to rapidly acquire and generalize knowledge to new tasks and situations. We suggest concrete challenges and promising routes toward these goals that can combine the strengths of recent neural network advances with more structured cognitive models. (shrink)