Within cognitive science, two approaches currently dominate the problem of modeling representations. The symbolic approach views cognition as computation involving symbolic manipulation. Connectionism, a special case of associationism, models associations using artificial neuron networks. Peter Gärdenfors offers his theory of conceptual representations as a bridge between the symbolic and connectionist approaches. Symbolic representation is particularly weak at modeling concept learning, which is paramount for understanding many cognitive phenomena. Concept learning is closely tied to the notion of similarity, which is also poorly served by the symbolic approach. Gärdenfors's theory of conceptual spaces presents a framework for representing information on the conceptual level. A conceptual space is built up from geometrical structures based on a number of quality dimensions. The main applications of the theory are on the constructive side of cognitive science: as a constructive model the theory can be applied to the development of artificial systems capable of solving cognitive tasks. Gärdenfors also shows how conceptual spaces can serve as an explanatory framework for a number of empirical theories, in particular those concerning concept formation, induction, and semantics. His aim is to present a coherent research program that can be used as a basis for more detailed investigations.

This edited book focuses on concepts and their applications using the theory of conceptual spaces, one of today’s most central tracks of cognitive science discourse. It features 15 papers based on topics presented at the Conceptual Spaces @ Work 2016 conference. The contributors interweave both theory and applications in their papers. Among the first mentioned are studies on metatheories, logical and systemic implications of the theory, as well as relations between concepts and language. Examples of the latter include explanatory models of paradigm shifts and evolution in science as well as dilemmas and issues of health, ethics, and education. The theory of conceptual spaces overcomes many translational issues between academic theoretization and practical applications. The paradigm is mainly associated with structural explanations, such as categorization and meronomy. However, the community has also been relating it to relations, functions, and systems. The book presents work that provides a geometric model for the representation of human conceptual knowledge that bridges the symbolic and the sub-conceptual levels of representation. The model has already proven to have a broad range of applicability beyond cognitive science and even across a number of disciplines related to concepts and representation.

This volume provides an overview of applications of conceptual spaces theory, beginning with an introduction to the modeling tool that unifies the chapters. The first section explores issues of linguistic semantics, including speakers’ negotiation of meaning. Further sections address computational and ontological aspects of constructing conceptual spaces, while the final section looks at philosophical applications. Domains include artificial intelligence and robotics, epistemology and philosophy of science, lexical semantics and pragmatics, agent-based simulation, perspectivism, framing, contrast, sensory modalities, and music, among others. This collection provides evidence of the wide application range of this theory of knowledge representation. The papers in this volume derive from international experts across different fields including philosophy, cognitive science, linguistics, robotics, computer science and geography. Each contributor has successfully applied conceptual spaces theory as a modeling tool in their respective areas of expertise. Graduates as well as researchers in the areas of epistemology, linguistics, geometric knowledge representation, and the mathematical modeling of cognitive processes should find this book of particular interest.

A novel cognitive theory of semantics that proposes that the meanings of words can be described in terms of geometric structures.

This open access book is a timely contribution in presenting recent issues, approaches, and results that are not only central to the highly interdisciplinary field of concept research but also particularly important to newly emergent paradigms and challenges. The contributors present a unique, holistic picture for the understanding and use of concepts from a wide range of fields including cognitive science, linguistics, philosophy, psychology, artificial intelligence, and computer science. The chapters focus on three distinct points of view that lie at the core of concept research: representation, learning, and application. The contributions present a combination of theoretical, experimental, computational, and applied methods that appeal to students and researchers working in these fields.

Offers an extended, improved version of Conceptual Metaphor Theory (CMT), updating it in the context of current linguistic theory.

Why do people like books, music, or movies that adhere consistently to genre conventions? Why is it hard for politicians to take positions that cross ideological boundaries? Why do we have dramatically different expectations of companies that are categorized as social media platforms as opposed to news media sites? The answers to these questions require an understanding of how people use basic concepts in their everyday lives to give meaning to objects, other people, and social situations and actions. In this book, a team of sociologists presents a groundbreaking model of concepts and categorization that can guide sociological and cultural analysis of a wide variety of social situations. Drawing on research in various fields, including cognitive science, computational linguistics, and psychology, the book develops an innovative view of concepts. It argues that concepts have meanings that are probabilistic rather than sharp, occupying fuzzy, overlapping positions in a “conceptual space.” Measurements of distances in this space reveal our mental representations of categories. Using this model, important yet commonplace phenomena such as our routine buying decisions can be quantified in terms of the cognitive distance between concepts. Concepts and Categories provides an essential set of formal theoretical tools and illustrates their application using an eclectic set of methodologies, from micro-level controlled experiments to macro-level language processing. It illuminates how explicit attention to concepts and categories can give us a new understanding of everyday situations and interactions.