Reinforcement Learning for Optimal Feedback Control develops model-based and data-driven reinforcement learning methods for solving optimal control problems in nonlinear deterministic dynamical systems.
This book presents a methodology based on inverse problems for use in solutions for fault diagnosis in control systems, combining tools from mathematics, physics, computational and mathematical modeling, optimization and computational intelligence.
Since nonsmooth optimization problems arise in a diverse range of real-world applications, the potential impact of efficient methods for solving such problems is undeniable.
This book covers not only foundational materials but also the most recent progresses made during the past few years on the area of machine learning algorithms.
This monograph introduces the authors' work on model predictive control system design using extended state space and extended non-minimal state space approaches.
This book introduces the theory and applications of uncertain optimal control, and establishes two types of models including expected value uncertain optimal control and optimistic value uncertain optimal control.
This edited book focuses on non-classical logics and their applications, highlighting the rapid advances and the new perspectives that are emerging in this area.
This book provides a practice-driven, yet rigorous approach to executive management decision-making that performs well even under unpredictable conditions.
This book proposes, for the first time, a basic formulation for structural control that takes into account the stochastic dynamics induced by engineering excitations in the nature of non-stationary and non-Gaussian processes.
The book offers an in-depth study of the translation of vote counts into seat numbers in proportional representation systems - an approach guided by practical needs.
This book reviews the state-of-the-art developments in nature-inspired algorithms and their applications in various disciplines, ranging from feature selection and engineering design optimization to scheduling and vehicle routing.
Das vorliegende Lehrbuch ist eine Einführung in die globale Optimierung, die mathematische Sachverhalte einerseits stringent behandelt, sie aber andererseits auch sehr ausführlich motiviert und mit 75 Abbildungen illustriert.
Questo libro – primo di due volumi – presenta oltre 250 esercizi scelti di algebra ricavati dai compiti d'esame dei corsi di Aritmetica tenuti dagli autori all'Università di Pisa.
This collection of essays represents responses by over eighty scholars to an unusual request: give your high level assessment of the field of economic design, as broadly construed.
This book constitutes the refereed post-conference proceedings of the 6th International Conference on Variable Neighborhood Search, ICVNS 2018, held in Sithonia, Greece, in October 2018.
This book discusses unconstrained optimization with R-a free, open-source computing environment, which works on several platforms, including Windows, Linux, and macOS.
This book offers a systematic and rigorous treatment of continuous-time Markov decision processes, covering both theory and possible applications to queueing systems, epidemiology, finance, and other fields.
The book discusses essential topics in industrial and applied mathematics such as image processing with a special focus on medical imaging, biometrics and tomography.
This book constitutes revised selected papers from the 16th International Conference on Group Decision and Negotiation, GDN 2016, held in Bellingham, WA, USA, in June 2016.
This book is devoted to the mathematical analysis of the numerical solution of boundary integral equations treating boundary value, transmission and contact problems arising in elasticity, acoustic and electromagnetic scattering.
Researchers and practitioners in computer science, optimization, operations research and mathematics will find this book useful as it illustrates optimization models and solution methods in discrete, non-differentiable, stochastic, and nonlinear optimization.
Focused on the logistics and transportation operations within a supply chain, this book brings together the latest models, algorithms, and optimization possibilities.
This book is designed as a textbook, suitable for self-learning or for teaching an upper-year university course on derivative-free and blackbox optimization.
The Proceedings volume contains 16 contributions to the IMPA conference "e;New Trends in Parameter Identification for Mathematical Models"e;, Rio de Janeiro, Oct 30 - Nov 3, 2017, integrating the "e;Chemnitz Symposium on Inverse Problems on Tour"e;.
This book provides an overview of classical actuarial techniques, including material that is not readily accessible elsewhere such as the Ammeter risk model and the Markov-modulated risk model.
This book focuses on the design of efficient & dynamic methods to allocate divisible resources under various auction mechanisms, discussing their applications in power & microgrid systems and the V2G & EV charging coordination problems in smart grids.
This is the first book to provide a comprehensive and systematic introduction to the ranking methods for interval-valued intuitionistic fuzzy sets, multi-criteria decision-making methods with interval-valued intuitionistic fuzzy sets, and group decision-making methods with interval-valued intuitionistic fuzzy preference relations.
This book provides a literature review of techniques used to pass from continuous to combinatorial space, before discussing a detailed example with individual steps of how cuckoo search (CS) can be adapted to solve combinatorial optimization problems.
This book covers some important topics in the construction of computable general equilibrium (CGE) models and examines use of these models for the analysis of economic policies, their properties, and their implications.
Due to an ever-decreasing supply in raw materials and stringent constraints on conventional energy sources, demand for lightweight, efficient and low-cost structures has become crucially important in modern engineering design.
The Gradient Test: Another Likelihood-Based Test presents the latest on the gradient test, a large-sample test that was introduced in statistics literature by George R.
Mathematica by Example, Fifth Edition is an essential desk reference for the beginning Mathematica user, providing step-by-step instructions on achieving results from this powerful software tool.
Providing an alternative to engineering-focused resources in the area, Programming Mathematics Using MATLAB(R) introduces the basics of programming and of using MATLAB(R) by highlighting many mathematical examples.
This book is a compilation of recent research on distributed optimization algorithms for the integral load management of plug-in electric vehicle (PEV) fleets and their potential services to the electricity system.
This book provides a comprehensive introduction to nonlinear programming, featuring a broad range of applications and solution methods in the field of continuous optimization.
This book constitutes the refereed proceedings of the 19th International Conference on Group Decision and Negotiation, GDN 2019, held in Loughborough, UK, in June 2019.
