Focuses on the integration of ordinary differential equations within the interval constraints framework, which for this purpose is extended with the formalism of Constraint Satisfaction Differential Problems. Such a framework allows the specification of ordinary differential equations by means of constraints.

Differential-algebraic equations are the most natural way to mathematically model many complex systems in science and engineering. Once the model is derived, it is important to optimize the design parameters and control it in the most robust and efficient way to maximize performance. This book presents the latest theory and numerical methods for the optimal control of differential-algebraic equations. The following features are presented in a readable fashion so the results are accessible to the widest audience: the most recent theory, written by leading experts from a number of academic and nonacademic areas and departments; several state-of-the-art numerical methods; and real-world applications.

Some applications of discrepancy analysis are suggested. Qualitative linear models (QLMs) are introduced as qualitative versions of systems of first-order, linear differential equations. All variables, including signals, are represented by qualitative interval labels (QILs), which combine the advantages of discrete sets of labels and interval labels. A form of qualitative reasoning, based on perturbations to labels and constraint satisfaction, is proposed and analysed."

This book addresses dynamics with inequalities comprehensively. The author develops the theory and application of dynamical systems that incorporate some kind of hard inequality constraint, such as mechanical systems with impact; electrical circuits with diodes (as diodes permit current flow in only one direction); and social and economic systems that involve natural or imposed limits (such as traffic flow, which can never be negative, or inventory, which must be stored within a given facility). This book demonstrates that hard limits - eschewed in most dynamical models - are natural models for many dynamic phenomena, and there are ways of creating differential equations with hard constraints that provide accurate models of many physical, biological, and economic systems. The author discusses how finite- and infinite-dimensional problems are treated in a unified way so the theory is applicable to both ordinary differential equations and partial differential equations.

This is the first book presenting a broad overview of parallelism in constraint-based reasoning formalisms. In recent years, an increasing number of contributions have been made on scaling constraint reasoning thanks to parallel architectures. The goal in this book is to overview these achievements in a concise way, assuming the reader is familiar with the classical, sequential background. It presents work demonstrating the use of multiple resources from single machine multi-core and GPU-based computations to very large scale distributed execution platforms up to 80,000 processing units. The contributions in the book cover the most important and recent contributions in parallel propositional satisfiability (SAT), maximum satisfiability (MaxSAT), quantified Boolean formulas (QBF), satisfiability modulo theory (SMT), theorem proving (TP), answer set programming (ASP), mixed integer linear programming (MILP), constraint programming (CP), stochastic local search (SLS), optimal path finding with A*, model checking for linear-time temporal logic (MC/LTL), binary decision diagrams (BDD), and model-based diagnosis (MBD). The book is suitable for researchers, graduate students, advanced undergraduates, and practitioners who wish to learn about the state of the art in parallel constraint reasoning.

The chapters in this book present the work of researchers, scientists, engineers, and teachers engaged with developing unified foundations, principles, and technologies for cyber-physical security. They adopt a multidisciplinary approach to solving related problems in next-generation systems, representing views from academia, government bodies, and industrial partners, and their contributions discuss current work on modeling, analyzing, and understanding cyber-physical systems.

This book constitutes the refereed proceedings of the 9th International Conference on Principles and Practice of Constraint Programming, CP 2003, held in Kinsale, Ireland in September/October 2003. The 48 revised full papers and 34 revised short papers presented together with 4 invited papers and 40 abstracts of contributions to the CP 2003 doctoral program were carefully reviewed and selected from 181 submissions. A wealth of recent results in computing with constraints is addressed ranging from foundational and methodological issues to solving real-world problems in a variety of application fields.