The book Model-Based Reasoning in Scientific Discovery, aims to explain how specific modeling practices employed by scientists are productive methods of creative changes in science. The study of diagnostic, visual, spatial, analogical, and temporal reasoning has demonstrated that there are many ways of performing intelligent and creative reasoning which cannot be described by classical logic alone. The study of these high-level methods of reasoning is situated at the crossroads of philosophy, artificial intelligence, cognitive psychology, and logic: at the heart of cognitive science. Model based reasoning promotes conceptual change because it is effective in abstracting, generating, and integrating constraints in ways that produce novel results. There are several key ingredients common to the various forms of model-based reasoning to be considered in this presentation. The models are intended as interpretations of target physical systems, processes, phenomena, or situations. The models are retrieved or constructed on the basis of potentially satisfying salient constraints of the target domain.In the modeling process, various forms of abstraction, such as limiting case, idealization, generalization, and generic modeling are utilized. Evaluation and adaptation take place in the light of structural of structural, causal, and/or functional constraint satisfaction and enhanced understanding of the target problem is obtained through the modeling process. Simulation can be used to produce new states and enable evaluation of behaviors, constraint satisfaction, and other factors. The book also addresses some of the main aspects of the concept of abduction, connecting it to the central epistemological question of hypothesis withdrawal in science and model-based reasoning, where abductive interferences exhibit their most appealing cognitive virtues. The most recent results and achievements in the above areas are illustrated in detail by the various contributors to the work, who are among the most respected researchers in philosophy, artificial intelligence and cognitive science.

The main part of the book is based on a one semester graduate course for students in mathematics. I have attempted to develop the theory of hyperbolic systems of differen tial equations in a systematic way, making as much use as possible ofgradient systems and their algebraic representation. However, despite the strong sim ilarities between the development of ideas here and that found in a Lie alge bras course this is not a book on Lie algebras. The order of presentation has been determined mainly by taking into account that algebraic representation and homomorphism correspondence with a full rank Lie algebra are the basic tools which require a detailed presentation. I am aware that the inclusion of the material on algebraic and homomorphism correspondence with a full rank Lie algebra is not standard in courses on the application of Lie algebras to hyperbolic equations. I think it should be. Moreover, the Lie algebraic structure plays an important role in integral representation for solutions of nonlinear control systems and stochastic differential equations yelding results that look quite different in their original setting. Finite-dimensional nonlin ear filters for stochastic differential equations and, say, decomposability of a nonlinear control system receive a common understanding in this framework."

This work is a revised and enlarged edition of a book with the same title published in Romanian by the Publishing House of the Romanian Academy in 1989. It grew out of lecture notes for a graduate course given by the author at the University if Ia i and was initially intended for students and readers primarily interested in applications of optimal control of ordinary differential equations. In this vision the book had to contain an elementary description of the Pontryagin maximum principle and a large number of examples and applications from various fields of science. The evolution of control science in the last decades has shown that its meth ods and tools are drawn from a large spectrum of mathematical results which go beyond the classical theory of ordinary differential equations and real analy ses. Mathematical areas such as functional analysis, topology, partial differential equations and infinite dimensional dynamical systems, geometry, played and will continue to play an increasing role in the development of the control sciences. On the other hand, control problems is a rich source of deep mathematical problems. Any presentation of control theory which for the sake of accessibility ignores these facts is incomplete and unable to attain its goals. This is the reason we considered necessary to widen the initial perspective of the book and to include a rigorous mathematical treatment of optimal control theory of processes governed by ordi nary differential equations and some typical problems from theory of distributed parameter systems."

In this book, a generic model in as far as possible mathematical closed-formis developed that predicts the behavior of large self-organizing robot groups (robot swarms) based on their control algorithm. In addition, an extensive subsumption of the relatively young and distinctive interdisciplinary research field of swarm robotics is emphasized. The connection to many related fields is highlighted and the concepts and methods borrowed from these fields are described shortly.

Organized Human Activity and Its Support by Computer proposes an answer to the question: what are computers for? With technical expertise, Anatol Holt analyzes human activity and its relevance to computer use. Holt interleaves a theory about the universal aspect of social life with a vision of how to harness computer power. This book is a culmination of a life of work that exemplifies two characteristics of the author: intellectual passion, and a concern for what matters to people. In the past thirty years, Holt has been a participant in the computing work at every level, from managing computer systems to developing commercial software to publishing theoretical articles in academic journals. His breadth of knowledge and experience makes possible the interweaving of theory and practice that shapes the fabric of this book. People often make a false opposition between theory and practice. In this case, it is a synergy: practice guides the theory, and the theory is grounded in its application.' Terry Winograd, Stanford University Organized Human Activity and Its Support by Computer will be of interest to those concerned with computers, especially those with and interest in groupware'. Particular relevance to social scientists, management scientists, students of law, and philosophers are also addressed. Though technical in spirit and method, this book does not expect significant prior computer knowledge of the reader.

This IMA Volume in Mathematics and its Applications ESSAYS ON MATHEMATICAL ROBOTICS is based on the proceedings of a workshop that was an integral part of the 1992-93 IMA program on "Control Theory." The workshop featured a mathematicalintroductionto kinematics and fine motion planning; dynam- ics and control of kinematically redundant robot arms including snake-like robots, multi-fingered robotic hands; methods of non-holonomic motion planning for space robots, multifingered robot hands and mobile robots; new techniques in analytical mechanics for writing the dynamics of com- plicated multi-body systems subject to constraints on angular momentum or other non-holonomic constraints. In addition to papers representing proceedings of the Workshop, this volume contains several longer papers surveying developments of the intervening years. We thank John Baillieul, Shankar S. Sastry, and Hector J. Sussmann for organizing the workshop and editing the proceedings. We also take this opportunity to thank the National Science Foundation and the Army Research Office, whose financial support made the workshop possible. Avner Friedman Willard Miller, Jr.

Agriculture is changing rapidly all over the world. Intensification, diversification, optimizing scarce resources, integrated pest management, sustainability and climate change are key issues for agricultural institutes. The best solutions will be found by integrating disciplines. Organized thinking about future farming requires forecasting of the implications of alternative ways to farm and to develop agriculture. Systems thinking and systems simulation are indispensable tools for such integration and extrapolation. About 150 scientists and senior research leaders from all over the world participated in the symposium `Systems Approaches for Agricultural Development' to discuss these issues. The symposium reviewed the status of systems research and modeling in agriculture, with special reference to evaluating their efficacy and efficiency for achieving research goals, and to their application in developing countries, promoted international cooperation in modeling, and increased awareness of systems research and simulation. This book comprises the papers on the technical subjects. Well informed authors describe and illustrate how systems research was used to improve agricultural production systems of all continents and in diverse environments.

is both a player and a spectator, is explained here illuminatingly. With regard to logical ambiguities and paradoxes, which may show up in all these topics, he, like Locker, is of the opinion that, philosophically speaking all apory of a lower level have to be accepted an a higher level of thinking. After the above expositions of a more general purport we turn now to two contributions which are particularly focused on Bohr's concept of complementarity. First is the article of Hilgevoord who briefly and non-technically describes a short curriculum vitae of the concept beginning with Planck through Bohr to Heisenberg and Schrodinger. Included in this short story, of course, is the famous wave-particle duality and the paradox inherent in it many physicists are still saddled with. How this paradox was solved is explained here simply and clearly: first, generally by quantum mechanics where the disturbance theory of measurement was supposed to be of some relevance, and secondly, where this theory is further refmed leading to Bohr's conclusion of the essential unsolvability, and accordingly the completeness, of the statistical element of quantum mechanics. The reading of this short article may arouse questions and surmises whether complementarity has been ruminated by Bohr to tame the law of excluded middle dividing the well-defined content of position measurement from that of momentum measurement, just to mention one. Whatever it may be the idea of complementarity betrays the perplexity of the observing system in dealing with nature's complexity.

The disciplines of computer science and operations research (OR) have been linked since their origins, each contributing to the dramatic advances of the other. This work explores the connections between these key technologies: how high-performance computing methods have led to advances in OR de ployment, and how OR has contributed to the design and development of ad vanced systems. The collected writings-from researchers and practitioners in Computer Science, Operations Research, Management Science, and Artificial Intelligence-were among those delivered at the Fifth INFORMS Computer Science Technical Section Conference in Dallas, Texas, January 8-10, 1996. The articles advance both theory and practice. Presented are new approaches to complex problems based on: metaheuristics (neural networks, genetic al gorithms, and Tabu Search), optimization and mathematical programming, stochastic methods, constraint programming, and logical analysis. These ad vanced methodologies are applied to new applications in such areas as: telecom munications network design, financial engineering, manufacturing, project man agement, and forecasting, airline and machine scheduling, vehicle routing, mod eling and decision support systems. Featured is a remarkable paper by keynote speaker Fred Glover, creator of the Tabu Search family of metaheuristics. In it he develops the principles of memory-based heuristic methods, contrasts them with the popular genetic algorithms and simulated annealing, provides a sweeping survey of application vignettes, and points to promising avenues for future research."

The Background to the Institute The NATO Advanced Study Institute (ASI) 'People and Computers - Applying an Anthropocentric Approach to Integrated Production Systems and Organisations' came about after the distribution of a NATO fact sheet to BruneI University, which described the funding of ASls. The 'embryonic' director of the ASI brought this opportunity to the attention of the group of people, (some at BruneI and some from outside), who were together responsible for the teaching and management of the course in Computer Integrated Manufacturing (CIM) in BruneI's Department of Manufacturing and Engineering Systems. This course had been conceived in 1986 and was envisaged as a vehicle for teaching manufacturing engineering students the technology of information integration through project work. While the original idea of the course had also included the organisational aspects of CIM, the human factors questions were not considered. This shortcoming was recognised and the trial run of the course in 1988 contained some lectures on 'people' issues. The course team were therefore well prepared and keen to explore the People, Organisation and Technology (POT) aspects of computer integration, as applied to industrial production. A context was proposed which would allow the inclusion of people from many different backgrounds and which would open up time and space for reflection. The proposal to organise a NATO ASI was therefore welcomed by all concerned.

Some words about SCART 2000. SCART stands for science and art. SCART meetings are organized in a loose time sequence by an international group of scientists, most of them fluid-dynamicists. The first meeting was held in Hong-Kong, the second one in Berlin, and the third, and latest, one in Zurich. SCART meetings include a scientific conference and a number of art events. The intention is to restart a dialogue between scientists and artists which was so productive in the past. To achieve this goal several lectures given by scientists at the conference are intended for a broader public. In the proceedings they are denoted as SCART lectures. The artists in tum address the main theme of the conference with their contributions. The lectures at SCART 2000 covered the entire field of fluiddynamics, from laminar flows in biological systems to astrophysical events, such as the explosion of a neutron star. The main exhibition by Dutch and Swiss artists showed video and related art under the title 'Walking on Air'. Experimental music was performed in two concerts.

At the core of many engineering problems is the solution of sets of equa tions and inequalities, and the optimization of cost functions. Unfortunately, except in special cases, such as when a set of equations is linear in its un knowns or when a convex cost function has to be minimized under convex constraints, the results obtained by conventional numerical methods are only local and cannot be guaranteed. This means, for example, that the actual global minimum of a cost function may not be reached, or that some global minimizers of this cost function may escape detection. By contrast, interval analysis makes it possible to obtain guaranteed approximations of the set of all the actual solutions of the problem being considered. This, together with the lack of books presenting interval techniques in such a way that they could become part of any engineering numerical tool kit, motivated the writing of this book. The adventure started in 1991 with the preparation by Luc Jaulin of his PhD thesis, under Eric Walter's supervision. It continued with their joint supervision of Olivier Didrit's and Michel Kieffer's PhD theses. More than two years ago, when we presented our book project to Springer, we naively thought that redaction would be a simple matter, given what had already been achieved . . ."

Invoking the machinery of Control Theory to control a real-world plant means, on the basis of available a priori knowledge of the plant, design ing/selecting a feasible controller accomplishing the control objective. A priori knowledge about the plant is normally represented as a mathemat ical model, given by physical laws or measurement data. Such a model is inevitably uncertain, due to measurement errors, simplified models of natural laws, neglected dynamics, and the desire to get a model tractable for further computations. Control of Uncertain Systems is therefore an im portant issue, both practically and philosophically. Basically, two different approaches exist: Adaptive Control and Robust Control. On four beautiful summer days in June 1989, researchers from 12 coun tries gathered together in Bremen, West Germany, for a workshop devoted to these issues. 49 talks, invited and contributed, were presented. The present work collects 18 of these talks. (Program and original abstracts from the workshop are available as Report 209, Institute for Dynamical System.) The papers represent a broad scope of current trends in robust and adaptive control. Topics covered include: New directions in adaptive control, stability analysis of uncertain systems, robust and adaptive stabi lization, numerical methods, and topological aspects of robust control. The papers were carefully refereed and we would like to thank the referees for their efforts, which have resulted in substantial improvements."

This book bridges a gap between a rigorous mathematical approach to variational problems and the practical use of algorithms of structural optimization in engineering applications. The foundations of structural optimization are presented in sufficiently simple form as to make them available for practical use.

Changes in the second edition. The second edition differs from the first in that there is a full development of problems where the variance of the diffusion term and the jump distribution can be controlled. Also, a great deal of new material concerning deterministic problems has been added, including very efficient algorithms for a class of problems of wide current interest. This book is concerned with numerical methods for stochastic control and optimal stochastic control problems. The random process models of the controlled or uncontrolled stochastic systems are either diffusions or jump diffusions. Stochastic control is a very active area of research and new problem formulations and sometimes surprising applications appear regu larly. We have chosen forms of the models which cover the great bulk of the formulations of the continuous time stochastic control problems which have appeared to date. The standard formats are covered, but much emphasis is given to the newer and less well known formulations. The controlled process might be either stopped or absorbed on leaving a constraint set or upon first hitting a target set, or it might be reflected or "projected" from the boundary of a constraining set. In some of the more recent applications of the reflecting boundary problem, for example the so-called heavy traffic approximation problems, the directions of reflection are actually discontin uous. In general, the control might be representable as a bounded function or it might be of the so-called impulsive or singular control types."

Since the first edition of this book was published seven years ago, the field of modeling and simulation of communication systems has grown and matured in many ways, and the use of simulation as a day-to-day tool is now even more common practice. With the current interest in digital mobile communications, a primary area of application of modeling and simulation is now in wireless systems of a different flavor from the `traditional' ones. This second edition represents a substantial revision of the first, partly to accommodate the new applications that have arisen. New chapters include material on modeling and simulation of nonlinear systems, with a complementary section on related measurement techniques, channel modeling and three new case studies; a consolidated set of problems is provided at the end of the book.

This book considers signal processing and physical modeling meth ods for sound synthesis. Such methods are useful for example in mu sic synthesizers, computer sound cards, and computer games. Physical modeling synthesis has been commercialized for the first time about 10 years ago. Recently, it has been one of the most active research topics in musical acoustics and computer music. The authors of this book, Dr. Lutz Trautmann and Dr. Rudolf Rabenstein, are active researchers and inventors in the field of sound synthesis. Together they have developed a new synthesis technique, called the functional transformation method, which can be used for pro ducing musical sound in real time. Before this book, they have published over 20 papers on the topic in journals and conference proceedings. In this excellent textbook, the results are combined in a single volume. I believe that this will be considered an important step forward for the whole community.

This book focuses mainly on fractional Brownian fields and their extensions. It has been used to teach graduate students at Grenoble and Toulouse's Universities. It is as self-contained as possible and contains numerous exercises, with solutions in an appendix. After a foreword by Stephane Jaffard, a long first chapter is devoted to classical results from stochastic fields and fractal analysis. A central notion throughout this book is self-similarity, which is dealt with in a second chapter with a particular emphasis on the celebrated Gaussian self-similar fields, called fractional Brownian fields after Mandelbrot and Van Ness's seminal paper. Fundamental properties of fractional Brownian fields are then stated and proved. The second central notion of this book is the so-called local asymptotic self-similarity (in short lass), which is a local version of self-similarity, defined in the third chapter. A lengthy study is devoted to lass fields with finite variance. Among these lass fields, we find both Gaussian fields and non-Gaussian fields, called Levy fields. The Levy fields can be viewed as bridges between fractional Brownian fields and stable self-similar fields. A further key issue concerns the identification of fractional parameters. This is the raison d'etre of the statistics chapter, where generalized quadratic variations methods are mainly used for estimating fractional parameters. Last but not least, the simulation is addressed in the last chapter. Unlike the previous issues, the simulation of fractional fields is still an area of ongoing research. The algorithms presented in this chapter are efficient but do not claim to close the debate.

In this revised and expanded edition, Howard E. Jordan explains-in a clear manner-the technology of energy efficient electric motors including motor losses, testing, and efficiency labeling. He also discusses how to calculate the return on investment for an energy efficient motor in addition to several other subjects related to effective motor applications. New chapters explore permanent magnet synchronous motors and transistor pulse-width-modulated inverters. Engineers, purchasing managers, and executives who make decisions on motor selection will find this an invaluable reference.

From the reviews: "The book is an excellent combination of theory and real-world applications. Each application not only demonstrates the power of the theoretical results but also is important on its own behalf." IEEE Control Systems Magazine

Control of Discrete-event Systems provides a survey of the most important topics in the discrete-event systems theory with particular focus on finite-state automata, Petri nets and max-plus algebra. Coverage ranges from introductory material on the basic notions and definitions of discrete-event systems to more recent results. Special attention is given to results on supervisory control, state estimation and fault diagnosis of both centralized and distributed/decentralized systems developed in the framework of the Distributed Supervisory Control of Large Plants (DISC) project. Later parts of the text are devoted to the study of congested systems though fluidization, an over approximation allowing a much more efficient study of observation and control problems of timed Petri nets. Finally, the max-plus algebraic approach to the analysis and control of choice-free systems is also considered. Control of Discrete-event Systems provides an introduction to discrete-event systems for readers that are not familiar with this class of systems, but also provides an introduction to research problems and open issues of current interest to readers already familiar with them. Most of the material in this book has been presented during a Ph.D. school held in Cagliari, Italy, in June 2011.

There are several techniques to study noncooperative dynamic games, such as dynamic programming and the maximum principle (also called the Lagrange method). It turns out, however, that one way to characterize dynamic potential games requires to analyze inverse optimal control problems, and it is here where the Euler equation approach comes in because it is particularly well-suited to solve inverse problems. Despite the importance of dynamic potential games, there is no systematic study about them. This monograph is the first attempt to provide a systematic, self-contained presentation of stochastic dynamic potential games.

Simulation based on mathematical models plays a major role in computer aided design of integrated circuits (ICs). Decreasing structure sizes, increasing packing densities and driving frequencies require the use of refined mathematical models, and to take into account secondary, parasitic effects. This leads to very high dimensional problems which nowadays require simulation times too large for the short time-to-market demands in industry. Modern Model Order Reduction (MOR) techniques present a way out of this dilemma in providing surrogate models which keep the main characteristics of the device while requiring a significantly lower simulation time than the full model. With Model Reduction for Circuit Simulation we survey the state of the art in the challenging research field of MOR for ICs, and also address its future research directions. Special emphasis is taken on aspects stemming from miniturisations to the nano scale. Contributions cover complexity reduction using e.g., balanced truncation, Krylov-techniques or POD approaches. For semiconductor applications a focus is on generalising current techniques to differential-algebraic equations, on including design parameters, on preserving stability, and on including nonlinearity by means of piecewise linearisations along solution trajectories (TPWL) and interpolation techniques for nonlinear parts. Furthermore the influence of interconnects and power grids on the physical properties of the device is considered, and also top-down system design approaches in which detailed block descriptions are combined with behavioral models. Further topics consider MOR and the combination of approaches from optimisation and statistics, and the inclusion of PDE models with emphasis on MOR for the resulting partial differential algebraic systems. The methods which currently are being developed have also relevance in other application areas such as mechanical multibody systems, and systems arising in chemistry and to biology. The current number of books in the area of MOR for ICs is very limited, so that this volume helps to fill a gap in providing the state of the art material, and to stimulate further research in this area of MOR. Model Reduction for Circuit Simulation also reflects and documents the vivid interaction between three active research projects in this area, namely the EU-Marie Curie Action ToK project O-MOORE-NICE (members in Belgium, The Netherlands and Germany), the EU-Marie Curie Action RTN-project COMSON (members in The Netherlands, Italy, Germany, and Romania), and the German federal project System reduction in nano-electronics (SyreNe).

It is our pleasure to contribute the forewordto this book on symbiotic mul- robot organisms, which is largely based on the scienti?c ?ndings and exp- rations of two major EU research projects, Symbrion and Replicator, funded under the Seventh Framework Programme for Research and Technological 1 development (FP7) . FP7 emphasises consortia of European partners, tra- national collaboration, open coordination, ?exibility and excellence of - search and plays a leading role in multidisciplinary research and cooperative activities in Europe and beyond. Its impact is major in terms of integrating and structuring research communities across national borders to achieve a critical mass, providing the leverage for high-potential ?elds to take o?, and encouraging healthy competition at European level while avoiding unn- essary duplication of research capacities. Research proposals are evaluated through a demanding peer-review process and only the best are selected to be funded bythe EuropeanCommission(EC). The InformationandCom- nication Technologies(ICT) theme has set out a number of challengeswithin this context, which cover topics such as cognitive systems, modular robotics, adaptive systems and societies of artefacts. * Symbrion was selected following the Call "Pervasive Adaptation" of the 2 "Future and Emerging Technologies (FET)" programme area. Itstarted on 1 February 2008 and will run for 5 years. FET Proactive addresses evolutionary and revolutionary approaches through multidisciplinary - operation and investigates new future technology options in response to emerging societal and industrial needs and identi?es new drivers for - search.

Computational intelligence encompasses a wide variety of techniques that allow computation to learn, to adapt, and to seek. That is, they may be designed to learn information without explicit programming regarding the nature of the content to be retained, they may be imbued with the functionality to adapt to maintain their course within a complex and unpredictably changing environment, and they may help us seek out truths about our own dynamics and lives through their inclusion in complex system modeling. These capabilities place our ability to compute in a category apart from our ability to erect suspension bridges, although both are products of technological advancement and reflect an increased understanding of our world. In this book, we show how to unify aspects of learning and adaptation within the computational intelligence framework. While a number of algorithms exist that fall under the umbrella of computational intelligence, with new ones added every year, all of them focus on the capabilities of learning, adapting, and helping us seek. So, the term unified computational intelligence relates not to the individual algorithms but to the underlying goals driving them. This book focuses on the computational intelligence areas of neural networks and dynamic programming, showing how to unify aspects of these areas to create new, more powerful, computational intelligence architectures to apply to new problem domains.