1. Editors’ introduction -- Part I. Concepts, perception and knowledge. 2. Conceptual Spaces, Generalisation Probabilities and Perceptual Categorisation -- 3. Formalized Conceptual Spaces with a Geometric Representation of Correlations -- 4. Three levels of Naturalistic Knowledge -- 5. Convexity is a testable prediction in the theory of conceptual spaces: Reply to Hernández-Conde -- Part II. Evolving concepts. 6. On the Essentially Dynamic Nature of Concepts: Constant if Incremental Motion in Conceptual Spaces -- 7. Seeking for the Grasp. An Iterative Subdivision Model of Conceptualization -- Part III. Concepts and disciplines. 8. Lost in Space and Time: A Quest for Conceptual Spaces in Physics -- 9. Interacting Conceptual Spaces I: Grammatical Composition of Concepts -- 10. Magnitude and Number Sensitivity of the Approximate Number System in Conceptual Spaces. 11. José Hernandez-Conde: Reply to Gärdenfors.

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.