Computational Epistemology: From Reality to Wisdom is a journey through the mysteries of the Universe, the mind, wise intelligent machines, and reality as a whole with its extra spatial dimensions leading to a unifying theory of everything. Explore the limits of 'everything and nothing' as the truth emerges in simple concepts with their attached analogies, metaphors, and field equations.
This book is about nature considered as the totality of physical existence, the universe, and our present day attempts to understand it. If we see the universe as a network of networks of computational processes at many different levels of organization, what can we learn about physics, biology, cognition, social systems, and ecology expressed through interacting networks of elementary particles, atoms, molecules, cells, (and especially neurons when it comes to understanding of cognition and intelligence), organs, organisms and their ecologies? Regarding our computational models of natural phenomena Feynman famously wondered: “Why should it take an infinite amount of logic to figure out what one tiny piece of space/time is going to do?” Phenomena themselves occur so quickly and automatically in nature. Can we learn how to harness nature’s computational power as we harness its energy and materials? This volume includes a selection of contributions from the Symposium on Natural Computing/Unconventional Computing and Its Philosophical Significance, organized during the AISB/IACAP World Congress 2012, held in Birmingham, UK, on July 2-6, on the occasion of the centenary of Alan Turing’s birth. In this book, leading researchers investigated questions of computing nature by exploring various facets of computation as we find it in nature: relationships between different levels of computation, cognition with learning and intelligence, mathematical background, relationships to classical Turing computation and Turing’s ideas about computing nature - unorganized machines and morphogenesis. It addresses questions of information, representation and computation, interaction as communication, concurrency and agent models; in short this book presents natural computing and unconventional computing as extension of the idea of computation as symbol manipulation.
Edited by an international team of leading scholars, The Routledge Handbook of Social Epistemology is the first major reference work devoted to this growing field. The Handbook’s 46 chapters, all appearing in print here for the first time, and written by philosophers and social theorists from around the world, are organized into eight main parts: Historical Backgrounds The Epistemology of Testimony Disagreement, Diversity, and Relativism Science and Social Epistemology The Epistemology of Groups Feminist Epistemology The Epistemology of Democracy Further Horizons for Social Epistemology With lists of references after each chapter and a comprehensive index, this volume will prove to be the definitive guide to the burgeoning interdisciplinary field of social epistemology.
ACMES (Algorithms and Complexity in Mathematics, Epistemology, and Science) is a multidisciplinary conference series that focuses on epistemological and mathematical issues relating to computation in modern science. This volume includes a selection of papers presented at the 2015 and 2016 conferences held at Western University that provide an interdisciplinary outlook on modern applied mathematics that draws from theory and practice, and situates it in proper context. These papers come from leading mathematicians, computational scientists, and philosophers of science, and cover a broad collection of mathematical and philosophical topics, including numerical analysis and its underlying philosophy, computer algebra, reliability and uncertainty quantification, computation and complexity theory, combinatorics, error analysis, perturbation theory, experimental mathematics, scientific epistemology, and foundations of mathematics. By bringing together contributions from researchers who approach the mathematical sciences from different perspectives, the volume will further readers' understanding of the multifaceted role of mathematics in modern science, informed by the state of the art in mathematics, scientific computing, and current modeling techniques.
The first volume in this new series explores, through extensive co-operation, new ways of achieving the integration of science in all its diversity. The book offers essays from important and influential philosophers in contemporary philosophy, discussing a range of topics from philosophy of science to epistemology, philosophy of logic and game theoretical approaches. It will be of interest to philosophers, computer scientists and all others interested in the scientific rationality.
By applying research in artificial intelligence to problems in the philosophy of science, Paul Thagard develops an exciting new approach to the study of scientific reasoning. This approach uses computational ideas to shed light on how scientific theories are discovered, evaluated, and used in explanations. Thagard describes a detailed computational model of problem solving and discovery that provides a conceptually rich yet rigorous alternative to accounts of scientific knowledge based on formal logic, and he uses it to illuminate such topics as the nature of concepts, hypothesis formation, analogy, and theory justification.
Epistemology, the philosophy of knowledge, is at the core of many of the central debates and issues in philosophy, interrogating the notions of truth, objectivity, trust, belief and perception. The Routledge Companion to Epistemology provides a comprehensive and the up-to-date survey of epistemology, charting its history, providing a thorough account of its key thinkers and movements, and addressing enduring questions and contemporary research in the field. Organized thematically, the Companion is divided into ten sections: Foundational Issues, The Analysis of Knowledge, The Structure of Knowledge, Kinds of Knowledge, Skepticism, Responses to Skepticism, Knowledge and Knowledge Attributions, Formal Epistemology, The History of Epistemology, and Metaepistemological Issues. Seventy-eight chapters, each between 5000 and 7000 words and written by the world’s leading epistemologists, provide students with an outstanding and accessible guide to the field. Designed to fit the most comprehensive syllabus in the discipline, this text will be an indispensible resource for anyone interested in this central area of philosophy. The Routledge Companion to Epistemology is essential reading for students of philosophy.
Offering a wide range of programming examples implemented in MATLAB, Computational Intelligence Paradigms: Theory and Applications Using MATLAB presents theoretical concepts and a general framework for computational intelligence (CI) approaches, including artificial neural networks, fuzzy systems, evolutionary computation, genetic algorithms and pr
Applying Computational Intelligence for Social Good: Track, Understand and Build a Better World, Volume 132 presents views on how Computational Intelligent and ICT technologies can be applied to ease or solve social problems by sharing examples of research results from studies of social anxiety, environmental issues, mobility of the disabled, and problems in social safety. Sample chapters in this release include Why is implementing Computational Intelligence for social good so challenging? Principles and its Application, Smart crisis management system for road accidents using Geo-Spacial Machine Learning Techniques, Residential Energy Management System (REMS) Using Machine Learning, Text-Based Personality Prediction using XLNet, and much more. - Explores a number of key themes, including self-organization, complex adaptive systems, and emergent computation for solving socially relevant problems - Focuses on Forecasting applications, Human Behavior and Critics response analysis in social forums, Healthcare monitoring Systems, Disaster Management, Industrial management, and most recently, Epidemics and Outbreaks - Brings together many different aspects of the current research on intelligence technologies, such as neural networks, support vector machines, fuzzy logic, and evolutionary computation
