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Optimal Search For Moving Targets In Continuous Time And Space Using Consistent Approximations

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Optimal Search For Moving Targets

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Author : Lawrence D. Stone
language : en
Publisher: Springer
Release Date : 2016-04-06

Optimal Search For Moving Targets written by Lawrence D. Stone and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-04-06 with Business & Economics categories.

This book begins with a review of basic results in optimal search for a stationary target. It then develops the theory of optimal search for a moving target, providing algorithms for computing optimal plans and examples of their use. Next it develops methods for computing optimal search plans involving multiple targets and multiple searchers with realistic operational constraints on search movement. These results assume that the target does not react to the search. In the final chapter there is a brief overview of mostly military problems where the target tries to avoid being found as well as rescue or rendezvous problems where the target and the searcher cooperate. Larry Stone wrote his definitive book Theory of Optimal Search in 1975, dealing almost exclusively with the stationary target search problem. Since then the theory has advanced to encompass search for targets that move even as the search proceeds, and computers have developed sufficient capability to employ the improved theory. In this book, Stone joins Royset and Washburn to document and explain this expanded theory of search. The problem of how to search for moving targets arises every day in military, rescue, law enforcement, and border patrol operations.

Optimal Search For Moving Targets In Continuous Time And Space Using Consistent Approximations

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Author : Joseph Carl Foraker
language : en
Publisher:
Release Date : 2011

Optimal Search For Moving Targets In Continuous Time And Space Using Consistent Approximations written by Joseph Carl Foraker and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with Operations research categories.

We show how to formulate many continuous time-and-space search problems as generalized optimal control problems, where multiple searchers look for multiple targets. Speci cally, we formulate problems in which we minimize the probability that all of the searchers fail to detect any of the targets during the planning horizon, and problems in which we maximize the expected number of targets detected. We construct discretization schemes to solve these continuous time-and-space problems, and prove that they are consistent approximations. Consistency ensures that global minimizers, local minimizers, and stationary points of the discretized problems converge to global minimizers, local minimizers, and stationary points, respectively, of the original problems. We also investigate the rate of convergence of algorithms based on discretization schemes as a computing budget tends to in nity. We provide numerical results to show that our discretization schemes are computationally tractable, including examples with three searchers and ten targets. We develop three heuristics for real-time search planning, one based on our discretization schemes, and two based on polynomial tting methods, and compare the three methods to determine which solution technique would be best suited for use onboard unmanned platforms for automatic route generation for search missions.

Applied And Computational Optimal Control

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Author : Kok Lay Teo
language : en
Publisher: Springer Nature
Release Date : 2021-05-24

Applied And Computational Optimal Control written by Kok Lay Teo and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-24 with Mathematics categories.

The aim of this book is to furnish the reader with a rigorous and detailed exposition of the concept of control parametrization and time scaling transformation. It presents computational solution techniques for a special class of constrained optimal control problems as well as applications to some practical examples. The book may be considered an extension of the 1991 monograph A Unified Computational Approach Optimal Control Problems, by K.L. Teo, C.J. Goh, and K.H. Wong. This publication discusses the development of new theory and computational methods for solving various optimal control problems numerically and in a unified fashion. To keep the book accessible and uniform, it includes those results developed by the authors, their students, and their past and present collaborators. A brief review of methods that are not covered in this exposition, is also included. Knowledge gained from this book may inspire advancement of new techniques to solve complex problems that arise in the future. This book is intended as reference for researchers in mathematics, engineering, and other sciences, graduate students and practitioners who apply optimal control methods in their work. It may be appropriate reading material for a graduate level seminar or as a text for a course in optimal control.

Bulletin Of The Atomic Scientists

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Author :
language : en
Publisher:
Release Date : 1961-05

Bulletin Of The Atomic Scientists written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1961-05 with categories.

The Bulletin of the Atomic Scientists is the premier public resource on scientific and technological developments that impact global security. Founded by Manhattan Project Scientists, the Bulletin's iconic "Doomsday Clock" stimulates solutions for a safer world.

Scientific And Technical Aerospace Reports

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Author :
language : en
Publisher:
Release Date : 1994

Scientific And Technical Aerospace Reports written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994 with Aeronautics categories.

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Author : 日本オペレーションズ・リサーチ学会
language : en
Publisher:
Release Date : 2003

written by 日本オペレーションズ・リサーチ学会 and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with Operations research categories.

Reinforcement Learning And Dynamic Programming Using Function Approximators

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Author : Lucian Busoniu
language : en
Publisher: CRC Press
Release Date : 2017-07-28

Reinforcement Learning And Dynamic Programming Using Function Approximators written by Lucian Busoniu and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-28 with Computers categories.

From household appliances to applications in robotics, engineered systems involving complex dynamics can only be as effective as the algorithms that control them. While Dynamic Programming (DP) has provided researchers with a way to optimally solve decision and control problems involving complex dynamic systems, its practical value was limited by algorithms that lacked the capacity to scale up to realistic problems. However, in recent years, dramatic developments in Reinforcement Learning (RL), the model-free counterpart of DP, changed our understanding of what is possible. Those developments led to the creation of reliable methods that can be applied even when a mathematical model of the system is unavailable, allowing researchers to solve challenging control problems in engineering, as well as in a variety of other disciplines, including economics, medicine, and artificial intelligence. Reinforcement Learning and Dynamic Programming Using Function Approximators provides a comprehensive and unparalleled exploration of the field of RL and DP. With a focus on continuous-variable problems, this seminal text details essential developments that have substantially altered the field over the past decade. In its pages, pioneering experts provide a concise introduction to classical RL and DP, followed by an extensive presentation of the state-of-the-art and novel methods in RL and DP with approximation. Combining algorithm development with theoretical guarantees, they elaborate on their work with illustrative examples and insightful comparisons. Three individual chapters are dedicated to representative algorithms from each of the major classes of techniques: value iteration, policy iteration, and policy search. The features and performance of these algorithms are highlighted in extensive experimental studies on a range of control applications. The recent development of applications involving complex systems has led to a surge of interest in RL and DP methods and the subsequent need for a quality resource on the subject. For graduate students and others new to the field, this book offers a thorough introduction to both the basics and emerging methods. And for those researchers and practitioners working in the fields of optimal and adaptive control, machine learning, artificial intelligence, and operations research, this resource offers a combination of practical algorithms, theoretical analysis, and comprehensive examples that they will be able to adapt and apply to their own work. Access the authors' website at www.dcsc.tudelft.nl/rlbook/ for additional material, including computer code used in the studies and information concerning new developments.