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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.
This Festschrift volume is published in memory of William W. McCune who passed away in 2011. William W. McCune was an accomplished computer scientist all around but especially a fantastic system builder and software engineer. The volume includes 13 full papers, which are presenting research in all aspects of automated reasoning and its applications to mathematics. These papers have been thoroughly reviewed and selected out of 15 submissions received in response to the call for paper issued in September 2011. The topics covered are: strategies, indexing, superposition-based theorem proving, model building, application of automated reasoning to mathematics, as well as to program verification, data mining, and computer formalized mathematics.
Distributed and multi-agent systems are becoming more and more the focus of attention in artificial intelligence research and have already found their way into many practical applications. An important prerequisite for their success is an ability to flexibly adapt their behavior via intelligent cooperation. Successful reasoning about and within a multi-agent system is therefore paramount to achieve intelligent behavior. Distributed Constraint Satisfaction Problems (DCSPs) and Distributed Constraint Optimization (minimization) Problems (DCOPs) are perhaps ubiquitous in distributed systems in dynamic environments. Many important problems in distributed environments and systems, such as action coordination, task scheduling and resource allocation, can be formulated and solved as DCSPs and DCOPs. Therefore, techniques for solving DCSPs and DCOPs as well as strategies for automated reasoning in distributed systems are indispensable tools in the research areas of distributed and multi-agent systems. They also provide promising frameworks to deal with the increasingly diverse range of distributed real world problems emerging from the fast evolution of communication technologies. The volume is divided in two parts. One part contains papers on distributed constraint problems in multi-agent systems. The other part presents papers on Agents and Automated Reasoning.
In this ambitious study, David Corfield attacks the widely held view that it is the nature of mathematical knowledge which has shaped the way in which mathematics is treated philosophically and claims that contingent factors have brought us to the present thematically limited discipline. Illustrating his discussion with a wealth of examples, he sets out a variety of approaches to new thinking about the philosophy of mathematics, ranging from an exploration of whether computers producing mathematical proofs or conjectures are doing real mathematics, to the use of analogy, the prospects for a Bayesian confirmation theory, the notion of a mathematical research programme and the ways in which new concepts are justified. His inspiring book challenges both philosophers and mathematicians to develop the broadest and richest philosophical resources for work in their disciplines and points clearly to the ways in which this can be done.
Based on fundamental principles from mathematics, linear systems, and signal analysis, digital signal processing (DSP) algorithms are useful for extracting information from signals collected all around us. Combined with today’s powerful computing capabilities, they can be used in a wide range of application areas, including engineering, communications, geophysics, computer science, information technology, medicine, and biometrics. Updated and expanded, Digital Signal Processing with Examples in MATLAB®, Second Edition introduces the basic aspects of signal processing and presents the fundamentals of DSP. It also relates DSP to continuous signal processing, rather than treating it as an isolated operation. New to the Second Edition Discussion of current DSP applications New chapters on analog systems models and pattern recognition using support vector machines New sections on the chirp z-transform, resampling, waveform reconstruction, discrete sine transform, and logarithmic and nonuniform sampling A more comprehensive table of transforms Developing the fundamentals of DSP from the ground up, this bestselling text continues to provide readers with a solid foundation for further work in most areas of signal processing. For novices, the authors review the basic mathematics required to understand DSP systems and offer a brief introduction to MATLAB. They also include end-of-chapter exercises that not only provide examples of the topics discussed, but also introduce topics and applications not covered in the chapters.

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