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Anderson and Piccinini offer the most systematic, rigorous, and comprehensive account of computational implementation to date. Their robust mapping account holds that the key for establishing that a computation is physically implemented is that the physical states bear neither more nor less information than the computational states they map onto.
In The Physical Signature of Computation, Neal Anderson and Gualtiero Piccinini articulate and defend the robust mapping account--the most systematic, rigorous, and comprehensive account of computational implementation to date. Drawing in part from recent results in physical information theory, they argue that mapping accounts of implementation can be made adequate by incorporating appropriate physical constraints. According to the robust mapping account, the key constraint on mappings from physical to computational states--the key for establishing that a computation is physically implemented--is physical-computational equivalence: evolving physical states bear neither more nor less information about the evolving computation than do the computational states they map onto. When this highly nontrivial constraint is satisfied, among others that are spelled out as part of the account, a physical system can be said to implement a computation in a robust sense, which means that the system bears the physical signature of the computation. Anderson and Piccinini apply their robust mapping account to important questions in physical foundations of computation and cognitive science, including the alleged indeterminacy of computation, pancomputationalism, and the computational theory of mind. They show that physical computation is determinate, nontrivial versions of pancomputationalism fail, and cognition involves computation only insofar as neurocognitive systems bear the physical signature of specific computations. They also argue that both consciousness and physics outstrip computation.
In The Physical Signature of Computation, Neal Anderson and Gualtiero Piccinini articulate and defend the robust mapping account--the most systematic, rigorous, and comprehensive account of computational implementation to date. Drawing in part from recent results in physical information theory, they argue that mapping accounts of implementation can be made adequate by incorporating appropriate physical constraints. According to the robust mapping account, the key constraint on mappings from physical to computational states--the key for establishing that a computation is physically implemented--is physical-computational equivalence: evolving physical states bear neither more nor less information about the evolving computation than do the computational states they map onto. When this highly nontrivial constraint is satisfied, among others that are spelled out as part of the account, a physical system can be said to implement a computation in a robust sense, which means that the system bears the physical signature of the computation. Anderson and Piccinini apply their robust mapping account to important questions in physical foundations of computation and cognitive science, including the alleged indeterminacy of computation, pancomputationalism, and the computational theory of mind. They show that physical computation is determinate, nontrivial versions of pancomputationalism fail, and cognition involves computation only insofar as neurocognitive systems bear the physical signature of specific computations. They also argue that both consciousness and physics outstrip computation.
Computation permeates our world, but a satisfactory philosophical theory of what it is has been lacking. Gualtiero Piccinini presents a mechanistic account of what makes a physical system a computing system. He argues that computation does not entail representation or information-processing, although information-processing entails computation.
Computing systems are ubiquitous in contemporary life. Even the brain is thought to be a computing system of sorts. But what does it mean to say that a given organ or system "computes"? What is it about laptops, smartphones, and nervous systems that they are deemed to compute - and why does itseldom occur to us to describe stomachs, hurricanes, rocks, or chairs that way? These questions are key to laying the conceptual foundations of computational sciences, including computer science and engineering, and the cognitive and neural sciences.Oron Shagrir here provides an extended argument for the semantic view of computation, which states that semantic properties are involved in the nature of computing systems. The first part of the book provides general background. Although different in scope, these chapters have a common theme-namely,that the linkage between the mathematical theory of computability and the notion of physical computation is weak. The second part of the book reviews existing non-semantic accounts of physical computation. Shagrir analyze three influential accounts in greater depth and argues that none of theseaccounts is satisfactory, but each of them highlights certain key features of physical computation that he eventually adopts in his own semantic account of physical computation - a view that rests on a phenomenon known as simultaneous implementation (or "indeterminacy of computation"). Shagrircompletes the characterization of his account of computation and highlights the distinctive feature of computational explanations.
The Computational Theory of Mind says that the mind is a computing system. It has a long history going back to the idea that thought is a kind of computation. Its modern incarnation relies on analogies with contemporary computing technology and the use of computational models. It comes in many versions, some more plausible than others. This Element supports the theory primarily by its contribution to solving the mind-body problem, its ability to explain mental phenomena, and the success of computational modelling and artificial intelligence. To be turned into an adequate theory, it needs to be made compatible with the tractability of cognition, the situatedness and dynamical aspects of the mind, the way the brain works, intentionality, and consciousness.
A very active field of research is emerging at the frontier of statistical physics, theoretical computer science/discrete mathematics, and coding/information theory. This book sets up a common language and pool of concepts, accessible to students and researchers from each of these fields.
Although computation and the science of physical systems would appear to be unrelated, there are a number of ways in which computational and physical concepts can be brought together in ways that illuminate both. This volume examines fundamental questions which connect scholars from both disciplines: is the universe a computer? Can a universal computing machine simulate every physical process? What is the source of the computational power of quantum computers? Are computational approaches to solving physical problems and paradoxes always fruitful? Contributors from multiple perspectives reflecting the diversity of thought regarding these interconnections address many of the most important developments and debates within this exciting area of research. Both a reference to the state of the art and a valuable and accessible entry to interdisciplinary work, the volume will interest researchers and students working in physics, computer science, and philosophy of science and mathematics.
This volume contains papers presented at the Third International Conference on Computing and Information, ICCI '91, held at Carleton University in Ottawa, Canada, May 27-29, 1991. The conference was organized by the School of Computer Science at Carleton University, and was sponsored by the Natural Sciences and Engineering Research Council of Canada (NSERC) and Carleton University. ICCI '91 was an international forum for the presentation of original results in research, development, and applications in computing and information processing. The conference was aimed at both practitioners and theoreticians, and was organized into five streams: - Algorithms and complexity, - Databases and information systems, - Parallel processing and systems, - Distributed computing and systems, - Expert systems, artificial intelligence. This volume contains three invited papers, by E.C.R. Hehner, R.L. Probert, and S.J. Smith, and 71 selected papers.
Computational physics is a rapidly growing subfield of computational science, in large part because computers can solve previously intractable problems or simulate natural processes that do not have analytic solutions. The next step beyond Landau's First Course in Scientific Computing and a follow-up to Landau and Páez's Computational Physics, this text presents a broad survey of key topics in computational physics for advanced undergraduates and beginning graduate students, including new discussions of visualization tools, wavelet analysis, molecular dynamics, and computational fluid dynamics. By treating science, applied mathematics, and computer science together, the book reveals how this knowledge base can be applied to a wider range of real-world problems than computational physics texts normally address. Designed for a one- or two-semester course, A Survey of Computational Physics will also interest anyone who wants a reference on or practical experience in the basics of computational physics. Accessible to advanced undergraduates Real-world problem-solving approach Java codes and applets integrated with text Companion Web site includes videos of lectures