Recently, cellular automata machines with the size, speed, and flexibility for general experimentation at a moderate cost have become available to the scientific community. These machines provide a laboratory in which the ideas presented in this book can be tested and applied to the synthesis of a great variety of systems. Computer scientists and researchers interested in modeling and simulatio…
In questo testo si introducono i concetti di base per la modellistica numerica di problemi differenziali alle derivate parziali. Si considerano le classiche equazioni lineari ellittiche, paraboliche ed iperboliche, ma anche altre equazioni, quali quelle di diffusione e trasporto, di Navier-Stokes e le leggi di conservazione; si forniscono inoltre numerosi esempi fisici che stanno alla base di t…
Many science and engineering applications require the user to find solutions to systems of nonlinear constraints or to optimize a nonlinear function subject to nonlinear constraints. The field of global optimization is the study of methods to find all solutions to systems of nonlinear constraints and all global optima to optimization problems. Numerica is modeling language for global optimizati…
Originally presented as the author's thesis (doctoral--Harvard University, 1985).What are computers in education being used for? In this book, Cynthia Solomon takes a welcome look at the possibilities and issues of learning with and about computers in schools or in any other learning environment.Solomon focuses on the use of computers within the framework of recent innovative theories of learni…
Translation of: Matematica come narrazione : raccontare la matematica."This book introduces readers to the narrative structure of mathematical proofs and why mathematicians communicate that way, drawing examples from classic literature and employing metaphors and imagery"--OCLC-licensed vendor bibliographic record.
A source book for state-of-the-art MDL, including an extensive tutorial and recent theoretical advances and practical applications in fields ranging from bioinformatics to psychology.The process of inductive inference--to infer general laws and principles from particular instances--is the basis of statistical modeling, pattern recognition, and machine learning. The Minimum Descriptive Length (M…
"A Bradford book."An overview of the rapidly growing field of ant colony optimization that describes theoretical findings, the major algorithms, and current applications.The complex social behaviors of ants have been much studied by science, and computer scientists are now finding that these behavior patterns can provide models for solving difficult combinatorial optimization problems. The atte…
Category theory is a branch of pure mathematics that is becoming an increasingly important tool in theoretical computer science, especially in programming language semantics, domain theory, and concurrency, where it is already a standard language of discourse. Assuming a minimum of mathematical preparation, Basic Category Theory for Computer Scientists provides a straightforward presentation of…
Includes bibliographical references and index.Norbert Wiener's celebrated autobiography, available for the first time in one volume.OCLC-licensed vendor bibliographic record.
A description of perturbation-based methods developed in machine learning to augment novel optimization methods with strong statistical guarantees.In nearly all machine learning, decisions must be made given current knowledge. Surprisingly, making what is believed to be the best decision is not always the best strategy, even when learning in a supervised learning setting. An emerging body of wo…