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A new computationalist view of the mind that takes into account real-world issues of embodiment, interaction, physical implementation, and semantics.
What Is Computationalism The computational theory of mind (CTM), also known as computationalism, is a family of beliefs that may be found in the field of philosophy of mind. These views claim that the human mind is an information processing machine, and that cognition and consciousness together are a sort of computing. Computationalism is also known as the computational theory of mind (CTM). Warren McCulloch and Walter Pitts (1943) were the pioneers who originally proposed the idea that brain activity might be modeled as a computer process. They argued that computations in the neural networks may explain cognition. The theory was first proposed by Hilary Putnam in 1967 in its current iteration, and it was developed by Jerry Fodor, a PhD student of Putnam's who was also a philosopher and cognitive scientist during the 1960s, 1970s, and 1980s. Although the position was hotly debated in analytic philosophy in the 1990s due to the work of Putnam himself, John Searle, and others, it is still widely held in modern cognitive psychology, and many theorists in evolutionary psychology take it as a given. This viewpoint has been making a comeback in analytic philosophy throughout the 2000s and 2010s. How You Will Benefit (I) Insights, and validations about the following topics: Chapter 1: Computational Theory of Mind Chapter 2: Cognitive Science Chapter 3: Computation Chapter 4: Functionalism (Philosophy of Mind) Chapter 5: Artificial Consciousness Chapter 6: Connectionism Chapter 7: Cognitive Architecture Chapter 8: Neurophilosophy Chapter 9: Philosophy of Artificial Intelligence Chapter 10: Neural Computation (II) Answering the public top questions about computationalism. (III) Real world examples for the usage of computationalism in many fields. (IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of computationalism' technologies. Who This Book Is For Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of computationalism.
This book mainly focuses on the widely distributed nature of computational tools, models, and methods, ultimately related to the current importance of computational machines as mediators of cognition. An entirely new eco-cognitive approach to computation is offered, to underline the question of the overwhelming cognitive domestication of ignorant entities, which is persistently at work in our current societies. Eco-cognitive computationalism does not aim at furnishing an ultimate and static definition of the concepts of information, cognition, and computation, instead, it intends, by respecting their historical and dynamical character, to propose an intellectual framework that depicts how we can understand their forms of “emergence” and the modification of their meanings, also dealing with impressive unconventional non-digital cases. The new proposed perspective also leads to a clear description of the divergence between weak and strong levels of creative “abductive” hypothetical cognition: weak accomplishments are related to “locked abductive strategies”, typical of computational machines, and deep creativity is instead related to “unlocked abductive strategies”, which characterize human cognizers, who benefit from the so-called “eco-cognitive openness”.
Advocates of computers make sweeping claims for their inherently transformative power: new and different from previous technologies, they are sure to resolve many of our existing social problems, and perhaps even to cause a positive political revolution. In The Cultural Logic of Computation, David Golumbia, who worked as a software designer for more than ten years, confronts this orthodoxy, arguing instead that computers are cultural “all the way down”—that there is no part of the apparent technological transformation that is not shaped by historical and cultural processes, or that escapes existing cultural politics. From the perspective of transnational corporations and governments, computers benefit existing power much more fully than they provide means to distribute or contest it. Despite this, our thinking about computers has developed into a nearly invisible ideology Golumbia dubs “computationalism”—an ideology that informs our thinking not just about computers, but about economic and social trends as sweeping as globalization. Driven by a programmer’s knowledge of computers as well as by a deep engagement with contemporary literary and cultural studies and poststructuralist theory, The Cultural Logic of Computation provides a needed corrective to the uncritical enthusiasm for computers common today in many parts of our culture.
Can computers think? This book is intended to demonstrate that thinking, understanding, and intelligence are more than simply the execution of algorithms--that is, that machines cannot think. Written and edited by leaders in the fields of artificial intelligence and the philosophy of computing.
A defense of the computational explanation of cognition that relies on mechanistic philosophy of science and advocates for explanatory pluralism. In this book, Marcin Milkowski argues that the mind can be explained computationally because it is itself computational—whether it engages in mental arithmetic, parses natural language, or processes the auditory signals that allow us to experience music. Defending the computational explanation against objections to it—from John Searle and Hilary Putnam in particular—Milkowski writes that computationalism is here to stay but is not what many have taken it to be. It does not, for example, rely on a Cartesian gulf between software and hardware, or mind and brain. Milkowski's mechanistic construal of computation allows him to show that no purely computational explanation of a physical process will ever be complete. Computationalism is only plausible, he argues, if you also accept explanatory pluralism. Milkowski sketches a mechanistic theory of implementation of computation against a background of extant conceptions, describing four dissimilar computational models of cognition. He reviews other philosophical accounts of implementation and computational explanation and defends a notion of representation that is compatible with his mechanistic account and adequate vis à vis the four models discussed earlier. Instead of arguing that there is no computation without representation, he inverts the slogan and shows that there is no representation without computation—but explains that representation goes beyond purely computational considerations. Milkowski's arguments succeed in vindicating computational explanation in a novel way by relying on mechanistic theory of science and interventionist theory of causation.
Advocates of computers make sweeping claims for their inherently transformative power: new and different from previous technologies, they are sure to resolve many of our existing social problems, and perhaps even to cause a positive political revolution. In The Cultural Logic of Computation, David Golumbia, who worked as a software designer for more than ten years, confronts this orthodoxy, arguing instead that computers are cultural “all the way down”—that there is no part of the apparent technological transformation that is not shaped by historical and cultural processes, or that escapes existing cultural politics. From the perspective of transnational corporations and governments, computers benefit existing power much more fully than they provide means to distribute or contest it. Despite this, our thinking about computers has developed into a nearly invisible ideology Golumbia dubs “computationalism”—an ideology that informs our thinking not just about computers, but about economic and social trends as sweeping as globalization. Driven by a programmer’s knowledge of computers as well as by a deep engagement with contemporary literary and cultural studies and poststructuralist theory, The Cultural Logic of Computation provides a needed corrective to the uncritical enthusiasm for computers common today in many parts of our culture.
This series will include monographs and collections of studies devoted to the investigation and exploration of knowledge, information and data processing systems of all kinds, no matter whether human, (other) animal, or machine. Its scope is intended to span the full range of interests from classical problems in the philosophy of mind and philosophical psychology through issues in cognitive psychology and sociobiology (concerning the mental capabilities of other species) to ideas related to artificial intelligence and to computer science. While primary emphasis will be placed upon theoretical, conceptual and epistemological aspects of these problems and domains, empirical, experimental and methodological studies will also appear from time to time. One of the most, if not the most, exciting developments within cognitive science has been the emergence of connectionism as an alternative to the computational conception of the mind that tends to dominate the discipline. In this volume, John Tienson and Terence Horgan have brought together a fine collection of stimulating studies on connectionism and its significance. As the Introduction explains, the most pressing questions concern whether or not connectionism can provide a new conception of the nature of mentality. By focusing on the similarities and differences between connectionism and other approaches to cognitive science, the chapters of this book supply valuable resources that advance our understanding of these difficult issues. J.H.F.
The Oxford Handbook of Computational Economics and Finance provides a survey of both the foundations of and recent advances in the frontiers of analysis and action. It is both historically and interdisciplinarily rich and also tightly connected to the rise of digital society. It begins with the conventional view of computational economics, including recent algorithmic development in computing rational expectations, volatility, and general equilibrium. It then moves from traditional computing in economics and finance to recent developments in natural computing, including applications of nature-inspired intelligence, genetic programming, swarm intelligence, and fuzzy logic. Also examined are recent developments of network and agent-based computing in economics. How these approaches are applied is examined in chapters on such subjects as trading robots and automated markets. The last part deals with the epistemology of simulation in its trinity form with the integration of simulation, computation, and dynamics. Distinctive is the focus on natural computationalism and the examination of the implications of intelligent machines for the future of computational economics and finance. Not merely individual robots, but whole integrated systems are extending their "immigration" to the world of Homo sapiens, or symbiogenesis.
There is a long-lasting controversy concerning our mind and consciousness. Mind, Brain, Quantum AI, and the Multiverse proposes a connection between the mind, the brain, and the multiverse. The author introduces the main philosophical ideas concerning mind and freedom, and explains the basic principles of computer science, artificial intelligence of brain research, quantum physics, and quantum artificial intelligence. He indicates how we can provide an answer to the problem of the mind and consciousness by describing the nature of the physical world. His proposed explanation includes the Everett Many-Worlds theory. This book tries to avoid any non-essential metaphysical speculations. The text is an essential compilation of knowledge in philosophy, computer science, biology, and quantum physics. It is written for readers without any requirements in mathematics, physics, or computer science.