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This dissertation by Ulf Kargén focuses on scalable dynamic analysis of binary code, a critical area in computer science and information security. The work addresses the scalability challenges associated with dynamic slicing and instruction trace alignment, methods that are crucial for debugging, security auditing, and malware analysis. Dynamic slicing provides detailed information about instruction dependencies, while instruction trace alignment compares executions of similar programs. The research introduces innovative techniques to enhance scalability, reducing memory requirements without compromising speed. Additionally, the thesis applies these methods to improve fuzzing, a testing technique used to identify security vulnerabilities, achieving significant improvements in code coverage and bug detection. This work is intended for researchers and professionals in computer science, particularly those focused on program analysis and security.

Debugging in computer science. --- Dynamic programming.

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Dynamic programming is an efficient technique for solving optimization problems. It is based on breaking the initial problem down into simpler ones and solving these sub-problems, beginning with the simplest ones. A conventional dynamic programming algorithm returns an optimal object from a given set of objects. This book develops extensions of dynamic programming, enabling us to (i) describe the set of objects under consideration; (ii) perform a multi-stage optimization of objects relative to different criteria; (iii) count the number of optimal objects; (iv) find the set of Pareto optimal points for bi-criteria optimization problems; and (v) to study relationships between two criteria. It considers various applications, including optimization of decision trees and decision rule systems as algorithms for problem solving, as ways for knowledge representation, and as classifiers; optimization of element partition trees for rectangular meshes, which are used in finite element methods for solving PDEs; and multi-stage optimization for such classic combinatorial optimization problems as matrix chain multiplication, binary search trees, global sequence alignment, and shortest paths. The results presented are useful for researchers in combinatorial optimization, data mining, knowledge discovery, machine learning, and finite element methods, especially those working in rough set theory, test theory, logical analysis of data, and PDE solvers. This book can be used as the basis for graduate courses. .

Dynamic programming. --- Combinatorial optimization. --- Data mining. --- Engineering. --- Artificial intelligence. --- Computational Intelligence. --- Artificial Intelligence. --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Construction --- Industrial arts --- Technology --- Computational intelligence. --- Intelligence, Computational --- Artificial intelligence --- Soft computing

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River catchments and reservoirs play a central role in water security, food supply, flood risk management, hydropower generation, and ecosystem services; however, they are now under increasing pressure from population growth, economic activities, and changing climate means and extremes in many parts of the world. Adaptive management of river catchments and reservoirs requires an in-depth understanding of the impacts of future uncertainties and thus the development of robust, sustainable solutions to meet the needs of various stakeholders and the environment. To tackle the huge challenges in moving towards adaptive catchment management, this book presents the latest developments in cutting-edge knowledge, novel methodologies, innovative management strategies, and case studies, focusing on the following themes: reservoir dynamics and impact analysis of dam construction, optimal reservoir operation, climate change impacts on hydrological processes and water management, and integrated catchment management.

downscaling --- suspended sediment concentration --- modeling --- South-to-North Water Transfer Project --- sensitivity analysis --- simulation --- protection zone --- reservoirs --- mussel --- sediment regime --- resilience and robustness --- optimal flood control operation --- multi-objective model --- optimization --- scenario analysis --- floodplain vertical shape index --- aftereffect --- lentic habitats --- energy --- stochastic linear programming --- ?-constrained method --- Tekeze basin --- runoff --- cascade reservoirs --- costs and benefits --- sediment flushing efficiency --- vulnerability --- Heihe River Basin --- TB-MPC --- heating impact --- flushing efficiency --- system dynamics --- Indian Monsoon --- shaft spillway pipe --- integrated supply system modeling --- seasonal rainfall --- sediment management --- design and operation of the multipurpose reservoir --- Kappa distribution --- CO2 --- reliability --- uncertainty --- Yangtze River --- Markov chain --- the Yangtze River --- Environmental Fluid Dynamics Code (EFDC) model --- land and water resources --- integrated surface water-groundwater model --- Heilongjiang --- Kurobe River --- flow regime --- numerical simulation --- long distance water diversion --- tropical reservoir --- multi-stage stochastic optimization --- direct policy search --- inverted siphon --- environmental flow --- parameterization --- accompanying progressive optimality algorithm --- integrated management --- hydropower stations --- differential evolution algorithm --- sediment flushing of empty storage --- back propagation neural network --- NSGA-II --- two-dimensional bed evolution model --- real-time control --- upper Chao Phraya River Basin --- CMIP5 --- genetic algorithm --- dam --- irrigation --- CMIP3 --- water energy --- discharge --- the Jingjiang River Reach --- water environmental capacity (WEC) --- climate change --- shortage ratio: Vulnerability --- optimal scheduling --- hydrology --- Siemianówka --- ungauged basin --- game theory --- power function --- SWAT --- Dokan Dam --- natural flow regime --- bitterling --- reservoir flushing --- vertical profiles of concentration --- ratio curve --- partial gauged basin --- sediment load --- adaptive management --- water deficit --- the upper Yangtze River Basin --- Miyun Reservoir --- parameter relation --- stochastic dynamic programming --- NPP --- runoff response --- Narew River --- coupling model --- Langcang-Mekong River --- drinking water resources --- the Huangshi Reservoir --- reverse regulation --- nutrient uptake --- water resources allocation --- multi-agent of river basin --- HEC-ResPRM --- dynamic programming with progressive optimality algorithm (DP-POA) --- reservoir operation --- sea surface temperatures --- reservoir simulation model --- SWAT model --- El Niño/Southern Oscillation --- CORDEX-Africa --- hedging policy --- multi-objective optimization NSGA II --- reservoir --- general regression neural network --- flood control --- Jingjiang River Reach --- catchment modelling

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This book describes the latest advances in the theory of mean field games, which are optimal control problems with a continuum of players, each of them interacting with the whole statistical distribution of a population. While originating in economics, this theory now has applications in areas as diverse as mathematical finance, crowd phenomena, epidemiology, and cybersecurity.Because mean field games concern the interactions of infinitely many players in an optimal control framework, one expects them to appear as the limit for Nash equilibria of differential games with finitely many players, as the number of players tends to infinity. This book rigorously establishes this convergence, which has been an open problem until now. The limit of the system associated with differential games with finitely many players is described by the so-called master equation, a nonlocal transport equation in the space of measures. After defining a suitable notion of differentiability in the space of measures, the authors provide a complete self-contained analysis of the master equation. Their analysis includes the case of common noise problems in which all the players are affected by a common Brownian motion. They then go on to explain how to use the master equation to prove the mean field limit.This groundbreaking book presents two important new results in mean field games that contribute to a unified theoretical framework for this exciting and fast-developing area of mathematics.

Convergence. --- Mean field theory. --- Many-body problem --- Statistical mechanics --- Functions --- A priori estimate. --- Approximation. --- Bellman equation. --- Boltzmann equation. --- Boundary value problem. --- C0. --- Chain rule. --- Compact space. --- Computation. --- Conditional probability distribution. --- Continuous function. --- Convergence problem. --- Convex set. --- Cooperative game. --- Corollary. --- Decision-making. --- Derivative. --- Deterministic system. --- Differentiable function. --- Directional derivative. --- Discrete time and continuous time. --- Discretization. --- Dynamic programming. --- Emergence. --- Empirical distribution function. --- Equation. --- Estimation. --- Euclidean space. --- Folk theorem (game theory). --- Folk theorem. --- Heat equation. --- Hermitian adjoint. --- Implementation. --- Initial condition. --- Integer. --- Large numbers. --- Linearization. --- Lipschitz continuity. --- Lp space. --- Macroeconomic model. --- Markov process. --- Martingale (probability theory). --- Master equation. --- Mathematical optimization. --- Maximum principle. --- Method of characteristics. --- Metric space. --- Monograph. --- Monotonic function. --- Nash equilibrium. --- Neumann boundary condition. --- Nonlinear system. --- Notation. --- Numerical analysis. --- Optimal control. --- Parameter. --- Partial differential equation. --- Periodic boundary conditions. --- Porous medium. --- Probability measure. --- Probability theory. --- Probability. --- Random function. --- Random variable. --- Randomization. --- Rate of convergence. --- Regime. --- Scientific notation. --- Semigroup. --- Simultaneous equations. --- Small number. --- Smoothness. --- Space form. --- State space. --- State variable. --- Stochastic calculus. --- Stochastic control. --- Stochastic process. --- Stochastic. --- Subset. --- Suggestion. --- Symmetric function. --- Technology. --- Theorem. --- Theory. --- Time consistency. --- Time derivative. --- Uniqueness. --- Variable (mathematics). --- Vector space. --- Viscosity solution. --- Wasserstein metric. --- Weak solution. --- Wiener process. --- Without loss of generality.