Computational complexity is one of the most beautiful fields of modern mathematics, and it is increasingly relevant to other sciences ranging from physics to biology. But this beauty is often buried underneath layers of unnecessary formalism, and exciting recent results like interactive proofs, phase transitions, and quantum computing are usually considered too advanced for the typical student. This book bridges these gaps by explaining the deep ideas of theoretical computer science in a clear and enjoyable fashion, making them accessible to non-computer scientists and to computer scientists who finally want to appreciate their field from a new point of view. The authors start with a lucid and playful explanation of the P vs. NP problem, explaining why it is so fundamental, and so hard to resolve. They then lead the reader through the complexity of mazes and games; optimization in theory and practice; randomized algorithms, interactive proofs, and pseudorandomness; Markov chains and phase transitions; and the outer reaches of quantum computing. At every turn, they use a minimum of formalism, providing explanations that are both deep and accessible. The book is intended for graduate and undergraduate students, scientists from other areas who have long wanted to understand this subject, and experts who want to fall in love with this field all over again.

This book constitutes the refereed proceedings of the 9th Conference on Computability in Europe, CiE 2013, held in Milan, Italy, in July 2013. The 48 revised papers presented together with 1 invited lecture and 2 tutorials were carefully reviewed and selected with an acceptance rate of under 31,7%. Both the conference series and the association promote the development of computability-related science, ranging over mathematics, computer science and applications in various natural and engineering sciences such as physics and biology, and also including the promotion of related non-scientific fields such as philosophy and history of computing.

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.

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.

"On The Foundations of Computing is a technical, historical and conceptual investigation in the three main methodological approaches to the computational sciences: mathematical, engineering and experimental. The first part of the volume explores the background behind the formal understanding of computing, originating at the end of the XIX century, and it invesitagtes the formal origins and conceptual development of the notions of computation, algorithm and program. The second part of the volume overviews the construction of physical devices to perform automated tasks and it considers associated technical and conceptual issues. We start from the design and construction of the first generation of computing machines, explore their evolution and progress in engineering (for both hardware and software), and investigate their theoretical and conceptual problems. The third part of the volume analyses the methods and principles of experimental sciences founded on computational methods. We study the use of machines to perform scientific tasks, with particular reference to computer models and simulations. Each part aims at defining a notion of computational validity according to the corresponding methodological approach"--

This book shows you - through examples and puzzles and intriguing questions - how to make your computer reason logically. The automation of reasoning has advanced markedly in the past few decades, and this book discusses some of the remarkable successes that automated reasoning programs have had in tackling challenging problems in mathematics, logic, program verification, and circuit design. Because the intended audience includes students and teachers, the book provides many exercises as well as tutorial chapters that introduce readers to the field of logic and to automated reasoning in general. For more advanced researchers, the book presents challenging questions, many of which are still unanswered.

Artificial and Mathematical Theory of Computation is a collection of papers that discusses the technical, historical, and philosophical problems related to artificial intelligence and the mathematical theory of computation. Papers cover the logical approach to artificial intelligence; knowledge representation and common sense reasoning; automated deduction; logic programming; nonmonotonic reasoning and circumscription. One paper suggests that the design of parallel programming languages will invariably become more sophisticated as human skill in programming and software developments improves to attain faster running programs. An example of metaprogramming to systems concerns the design and control of operations of factory devices, such as robots and numerically controlled machine tools. Metaprogramming involves two design aspects: that of the activity of a single device and that of the interaction with other devices. One paper cites the application of artificial intelligence pertaining to the project "proof checker for first-order logic" at the Stanford Artificial Intelligence Laboratory. Another paper explains why the bisection algorithm widely used in computer science does not work. This book can prove valuable to engineers and researchers of electrical, computer, and mechanical engineering, as well as, for computer programmers and designers of industrial processes.

This Guide provides an ambitious state-of-the-art survey of the fundamental themes, problems, arguments and theories constituting the philosophy of computing. A complete guide to the philosophy of computing and information. Comprises 26 newly-written chapters by leading international experts. Provides a complete, critical introduction to the field. Each chapter combines careful scholarship with an engaging writing style. Includes an exhaustive glossary of technical terms. Ideal as a course text, but also of interest to researchers and general readers.

This book aims to illuminate theoretical and methodological advances in computational cultural neuroscience and the implications of these advances for philosophy. Philosophical studies in computational cultural neuroscience introduce core considerations such as culture and computation, and the role of scientific and technological progression for the advancement of cultural processes. The study of how cultural and biological factors shape human behaviour has been an important inquiry for centuries, and recent advances in the field of computational cultural neuroscience allow for novel insights into the computational foundations of cultural processes in the structural and functional organization of the nervous system. The author examines the computational foundations of the mind and brain across cultures and investigates the influence of culture on the computational mind and brain. The book explores recent advances in the field, providing novel insights on topics such as artificialism, reconstructionism, and intelligence. Philosophy of Computational Cultural Neuroscience is fascinating reading for students and academics in the field of neuroscience who wish to take a cultural or philosophical approach to their studies and research. This book is the winner of the International Cultural Neuroscience Society’s International Book Prize.

This book constitutes the thoroughly refereed post-conference proceedings of the International Conference on Nature of Computation and Communication, ICTCC 2014, held in November 2014 in Ho Chi Minh City, Vietnam. The 34 revised full papers presented were carefully reviewed and selected from over 100 submissions. The papers cover formal methods for self-adaptive systems and discuss natural approaches and techniques for computation and communication.