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Valuing Agroforestry Systems : Methods and Applications
Offers practical means for strengthening the economics and policy dimension of the agroforestry discipline. The applied economic methodologies encompass a wide variety of case studies including enterprise/farm budget models through Faustmann models, Policy Analysis Matrix, production function approach, risk assessment models, dynamic programming, linear programming, meta-modeling, contingent valuation, attribute-based choice experiments, econometric modeling, and institutional economic analysis. It is our belief that these methodologies help agroforestry students and professionals conduct rigorous assessment of economic and policy aspects of agroforestry systems and to produce less biased and more credible information. Furthermore, the economic and policy issues explored in the book – profitability, environmental benefits, risk reduction, household constraints, rural development, and institutional arrangements – are central to further agroforestry adoption in both tropical and temperate regions
Stochastic Control of Hereditary Systems and Applications
This research monograph develops the Hamilton-Jacobi-Bellman (HJB) theory through dynamic programming principle for a class of optimal control problems for stochastic hereditary differential systems. It is driven by a standard Brownian motion and with a bounded memory or an infinite but fading memory. The optimal control problems treated in this book include optimal classical control and optimal stopping with a bounded memory and over finite time horizon.
Simulation-based Algorithms for Markov Decision Processes
Markov decision process (MDP) models are widely used for modeling sequential decision-making problems that arise in engineering, economics, computer science, and the social sciences. It is well-known that many real-world problems modeled by MDPs have huge state and/or action spaces, leading to the notorious curse of dimensionality that makes practical solution of the resulting models intractable. In other cases, the system of interest is complex enough that it is not feasible to specify some of the MDP model parameters explicitly, but simulation samples are readily available (e.g., for random transitions and costs). For these settings, various sampling and population-based numerical algorithms have been developed recently to overcome the difficulties of computing an optimal solution in terms of a policy and/or value function.
Semiconcave Functions, Hamilton-Jacobi Equations, and Optimal Control
Semiconcavity is a natural generalization of concavity that retains most of the good properties known in convex analysis, but arises in a wider range of applications. This text is the first comprehensive exposition of the theory of semiconcave functions, and of the role they play in optimal control and Hamilton–Jacobi equations.
Scheduling Algorithms
Besides scheduling problems for single and parallel machines and shop scheduling problems the book covers advanced models involving due-dates, sequence dependent changeover times and batching. Also multiprocessor task scheduling and problems with multi-purpose machines are discussed. The methods used to solve these problems are linear programming, dynamic programming, branch-and-bound algorithms, and local search heuristics. Complexity results for different classes of deterministic scheduling problems are summerized.
RNA folding : Methods and protocols
Discusses the various levels of prediction and algorithmic approaches to RNA folding. The chapters in this book cover topics such as energy parameters of the nearest-neighbor (NN) energy model; classified dynamic programming to address exponential growth of candidate structures that an RNA molecule may fold into; sequence evolution and conserved structures among multiple RNA sequences; the latest framework capable of handling both positive and negative RNA sequence design objectives; and kinetic folding approaches that look at the dynamic nature of RNA folding
Recent Advances in Reinforcement Learning ; 8th European Workshop, EWRL 2008, Villeneuve d’Ascq, France, June 30-July 3, 2008, Revised and Selected Papers
They are dedicated to the field of and current researches in reinforcement learning.There was an air of excitement as substantial progress was reported in many areas including Computer Go, robotics, and fitted methods.
Recent Advances in Intrusion Detection ; 11th International Symposium, RAID 2008, Cambridge, MA, USA, September 15-17, 2008. Proceedings
This book is organized in topical sections on rootkit prevention, malware detection and prevention, high performance intrusion and evasion, Web application testing and evasion, alert correlation and worm detection, as well as anomaly detection and network traffic analysis.
Probability in electrical engineering and computer science : An application-driven course
This revised textbook motivates and illustrates the techniques of applied probability by applications in electrical engineering and computer science (EECS). The author presents information processing and communication systems that use algorithms based on probabilistic models and techniques, including web searches, digital links, speech recognition, GPS, route planning, recommendation systems, classification, and estimation. He then explains how these applications work and, along the way, provides the readers with the understanding of the key concepts and methods of applied probability. Python labs enable the readers to experiment and consolidate their understanding. The book includes homework, solutions, and Jupyter notebooks. This edition includes new topics such as Boosting, Multi-armed bandits, statistical tests, social networks, queuing networks, and neural networks. The companion website now has many examples of Python demos and also Python labs used in Berkeley.
Optimisation et contrôle stochastique appliqués à la finance = Optimization and stochastic control applied to finance
The objective and the originality of this book is to present the different aspects and methods used in the resolution of stochastic optimization problems with a view to more specific applications in finance: portfolio management, option hedging, optimal investment. . We have included some recent developments on the subject without seeking a priori the greatest generality. We wanted a gradual exposure of mathematical methods by first presenting the intuitive ideas and then precisely stating the results with full and detailed proofs.
Optimal Control of Constrained Piecewise Affine Systems
One of the most important and challenging problems in control is the derivation of systematic tools for the computation of controllers for constrained nonlinear systems that can guarantee closed-loop stability, feasibility, and optimality with respect to some performance index. This book focuses on the efficient and systematic computation of closed-form optimal controllers for the powerful class of fast-sampled constrained piecewise affine systems. These systems may exhibit rather complex behavior and are equivalent to many other hybrid system formalisms (combining continuous-valued dynamics with logic rules) reported in the literature. Furthermore, piecewise affine systems are a useful modeling tool that can capture general nonlinearities (e.g. by local approximation), constraints, saturations, switches, and other hybrid modeling phenomena. The first part of the book presents an introduction to the mathematical and control theoretical background material needed for the full understanding of the book.
Mathematics of Program Construction ; 8th International Conference, MPC 2006, Kuressaare, Estonia, July 3-5, 2006, Proceedings
This volume contains the proceedings of the 8th International Conference on Mathematics of ProgramConstruction, MPC 2006,held at Kuressaare, Estonia, July 3-5, 2006, colocated with the 11th International Conference on Algebraic Methodology and Software Technology, AMAST 2006, July 5-8, 2006. TheMPCconferencesaimtopromotethedevelopmentofmathematicalpr- ciples and techniques that are demonstrably useful and usable in the process of constructing computer programs. Topics of interest range from algorithmics to support for program construction in programming languages and systems.
Information Retrieval Technology ; 4th Asia Infomation Retrieval Symposium, AIRS 2008, Harbin, China, January 15-18, 2008 Revised Selected Papers
This book constitutes the thoroughly refereed post-conference proceedings of the 4th Asia Information Retrieval Symposium, AIRS 2008, held in Harbin, China, in May 2008.The 39 revised full papers and 43 revised poster papers presented were carefully reviewed and selected from 144 submissions. All current issues in information retrieval are addressed: applications, systems, technologies and theoretical aspects of information retrieval in text, audio, image, video and multi-media data. The papers are organized in topical sections on IR models image retrieval.
Fuzzy multi-criteria decision making : Theory and applications with recent developments
In trying to make a satisfactory decision when imprecise and multicriteria situations are involved, a decision maker has to use a fuzzy multicriteria decision making method. Fuzzy Multi-Criteria Decision Making (MCDM) presents fuzzy multiattribute and multiobjective decision-making methodologies by distinguished MCDM researchers. In summarizing the concepts and results of the most popular fuzzy multicriteria methods, using numerical examples, this work examines all the fuzzy multicriteria methods recently developed, such as fuzzy AHP, fuzzy TOPSIS, interactive fuzzy multiobjective stochastic linear programming, fuzzy multiobjective dynamic programming, grey fuzzy multiobjective optimization, fuzzy multiobjective geometric programming, and more.
Dynamic Programming : A Computational Tool
This book provides a practical introduction to computationally solving discrete optimization problems using dynamic programming. From the unusually numerous and varied examples presented, readers should more easily be able to formulate dynamic programming solutions to their own problems of interest. We also provide and describe the design, implementation, and use of a software tool, named DP2PN2Solver, that has been used to numerically solve all of the problems presented earlier in the book. This computational tool can be used by students to solve academic problems if this book is used in coursework, and by practitioners to solve many real-world problems if the state space is not too large.
Dynamic Asset Allocation with Forwards and Futures
DYNAMIC ASSET ALLOCATION WITH FORWARD AND FUTURES is an advanced text on the theory of forward and futures markets which aims at providing readers with a comprehensive knowledge of how prices are established and evolve over time, what optimal strategies one can expect from the participants, what characterizes such markets, and what major theoretical and practical differences distinguish futures from forward contracts. The book proposes an approach of these markets from the perspective of dynamic asset allocation and asset pricing theory within an inter-temporal framework. The main ingredients that are used are the assumed absence of frictions and arbitrage opportunities in financial and real markets, the uniqueness of the economic general equilibrium, when such an equilibrium is required and the tools of continuous time finance, namely martingale theory and stochastic dynamic programming. The scope of DYNAMIC ASSET ALLOCATION WITH FORWARD AND FUTURES is essentially theoretical, with emphasis on economic meaning and financial interpretation. Regarding investment and/or hedging, focus is on optimal strategies rather than on actual practice. Simulations, however, are performed when important insights can be delivered as to the practical relevance of some theoretical results. Also, optimal strategies using futures are shown to differ markedly from those using forwards. The following issues are examined: pure hedging, investment and hedging in complete or incomplete markets, currency risk, optimal spreading, presence of stochastic dividend or convenience yields, pricing of non-redundant futures or forwards by means of general equilibrium analysis, and revisiting of existing Capital Asset Pricing Models.
Controlled Markov Processes and Viscosity Solutions
This book is intended as an introduction to optimal stochastic control for continuous time Markov processes and to the theory of viscosity solutions. Stochastic control problems are treated using the dynamic programming approach. It approachs stochastic control problems by the method of dynamic programming. The fundamental equation of dynamic programming is a nonlinear evolution equation for the value function. For controlled Markov diffusion processes, this becomes a nonlinear partial differential equation of second order, called a Hamilton-Jacobi-Bellman (HJB) equation. Typically, the value function is not smooth enough to satisfy the HJB equation in a classical sense. Viscosity solutions provide framework in which to study HJB equations, and to prove continuous dependence of solutions on problem data. The theory is illustrated by applications from engineering, management science, and financial economics.
Combinatorics, Algorithms, Probabilistic and Experimental Methodologies ; 1st International Symposium, ESCAPE 2007, Hangzhou, China, April 7-9, 2007, Revised Selected Papers
This book address practical large data processing problems with different, and eventually converging, methodologies from major important disciplines such as computer science, combinatorics, and statistics. The symposium provides an interdisciplinary forum for researchers across their discipline boundaries to exchange their approaches, to search for ideas, methodologies, and tool boxes, to find better, faster and more accurate solutions thus fostering innovative ideas as well as to develop research agenda of common interest.
Combinatorial pattern matching ; Vol.4009) ; 17th Annual Symposium, CPM 2006, Barcelona, Spain, July 5-7, 2006, Proceedings
The book presents 33 revised full papers together with 3 invited talks, organized in topical sections on data structures, indexing data structures, probabilistic and algebraic techniques, applications in molecular biology, string matching, data compression, and dynamic programming
Combinatorial pattern matching ; 18th Annual Symposium, CPM 2007, London, Canada, July 9-11, 2007, Proceedings
This book presented original research contri- tions on computational pattern matching and analysis, data compression and compressed text processing, sufix arrays and trees, and computational biology. Combinatorial Pattern Matching addresses issues of searching and matching strings and more complicated patterns such as trees, regular expressions, graphs, point sets, and arrays.The goal is to derive non-trivial combinatorial properties of such structures and to exploit these properties in order to either achieve superior performance for the corresponding computational problems or pinpoint conditions under which searches cannot be performed eficiently.
