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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 open access book presents novel theoretical, empirical and experimental work exploring the nature of mental representations that support natural language production and understanding, and other manifestations of cognition. One fundamental question raised in the text is whether requisite knowledge structures can be adequately modeled by means of a uniform representational format, and if so, what exactly is its nature. Frames are a key topic covered which have had a strong impact on the exploration of knowledge representations in artificial intelligence, psychology and linguistics; cascades are a novel development in frame theory. Other key subject areas explored are: concepts and categorization, the experimental investigation of mental representation, as well as cognitive analysis in semantics. This book is of interest to students, researchers, and professionals working on cognition in the fields of linguistics, philosophy, and psychology.
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 book constitutes the thoroughly refereed papers of the Second International Conference on Applied Informatics, ICAI 2019, held in Madrid, Spain, in November 2019. The 37 full papers and one short paper were carefully reviewed and selected from 98 submissions. The papers are organized in topical sections on bioinformatics; data analysis; decision systems; health care information systems; IT Architectures; learning management systems; robotic autonomy; security services; socio-technical systems; software design engineering.
This volume constitutes revised selected papers from the four workshops collocated with the 19th International Conference on Software Engineering and Formal Methods, SEFM 2021, held virtually during December 6–10, 2021. The 21 contributed papers presented in this volume were carefully reviewed and selected from a total of 29 submissions. The book also contains 3 invited talks. SEFM 2021 presents the following four workshops: CIFMA 2021 - 3rd International Workshop on Cognition: Interdisciplinary Foundations, Models and Applications;CoSim-CPS 2021 - 5th Workshop on Formal Co-Simulation of Cyber-Physical Systems;OpenCERT 2021 - 10th International Workshop on Open Community approaches to Education, Research and Technology;ASYDE 2021 - 3rd International Workshop on Automated and verifiable Software sYstem Development. Due to the Corona pandemic this event was held virtually.
"Mahoney's starting point is the problem of essentialism in social science. Essentialism--the belief that the members of a category possess hidden properties ("essences") that make them members of the category and that endow them with a certain nature--is appropriate for scientific categories ("atoms", for instance) but not for human ones ("revolutions," for instance). Despite this, much social science research takes place from within an essentialist orientation; those who reject this assumption goes so far in the other direction as to reject the idea of an external reality, independent of human beings, altogether. Mahoney proposes an alternative approach that aspires to bridge this enduring rift in the social sciences between those who take a scientific approach and assume that social science categories correspond to external reality (and thus believe that the methods used in the natural sciences are generally appropriate for the social sciences) and those who take a constructivist approach and believe that because the categories used to understand the social world are humanly-constructed, they cannot possibly follow the science of the natural world. As the name suggests, scientific constructivism brings in aspects of both views and attempts to unite them. Drawing from cognitive science, it focuses on using the rational parts of our brain machinery to overcome the limitations and deeply seated biases (such as essentialism) of our evolved minds. Specifically, Mahoney puts forth a "set-theoretic analysis" that focuses on "sets" of categories as they exist in the mind that are also subject to the mathematical logic of set-theory. He spends the first four chapters of the book establishing the foundations and methods for set-theoretic analysis, the next four chapters looking and how this analysis fits with the existing tools of social science, and the final four chapters focusing on how this approach can be used to study and understand cases"--
This book addresses a longstanding impasse in problem solving research: if structured mental representations of problems are required for solving them, how do those arise and, if needed, change? The book argues that established theories underestimate this question due to methodological requirements. Proposing to momentarily suspend these requirements, including the focus on well-defined puzzle tasks, the book suggests to alternatively conduct exploratory studies with more complex, open-ended problems. It presents a qualitative case study of participants working for several days on a mental paper folding task designed to challenge them to construct their own representations. Charting their use of gestures, metaphors, and ever more complex descriptions, it carefully traces the chronology of their thinking. Combining in-depth empirical investigation with theory-building, the book proposes a framework of problem solving that goes beyond established models, accommodating associative, motivational, and affective factors. This book will be of great interest to researchers, academics, and postgraduate students in the fields of cognitive science, psychology, philosophy of mind and cognition, and cognitive artificial intelligence.
This book constitutes the refereed proceedings of the 13th International Conference on Graph Transformation, ICGT 2020, in Bergen, Norway, in June 2020.* The 16 research papers and 4 tool paper presented in this book were carefully reviewed and selected from 40 submissions. One invited paper is also included. The papers deal with the following topics: theoretical advances; application domains; and tool presentations. *The conference was held virtually due to the COVID-19 pandemic.
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.