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Information Search After Static or Moving Targets : Theory and Modern Applications.
Presents a probabilistic and information-theoretic framework for a search for static or moving targets in discrete time and space. Probabilistic Search for Tracking Targets uses an information-theoretic scheme to present a unified approach for known search methods to allow the development of new alg...
| Clasificación: | Libro Electrónico |
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| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Wiley,
2013.
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| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- Cover; Title Page; Copyright; Contents; List of figures; Preface; Notation and terms; Chapter 1 Introduction; 1.1 Motivation and applications; 1.2 General description of the search problem; 1.3 Solution approaches in the literature; 1.4 Methods of local search; 1.5 Objectives and structure of the book; References; Chapter 2 Problem of search for static and moving targets; 2.1 Methods of search and screening; 2.1.1 General definitions and notation; 2.1.2 Target location density for a Markovian search; 2.1.3 The search-planning problem; 2.2 Group-testing search.
- 2.2.1 General definitions and notation2.2.2 Combinatorial group-testing search for static targets; 2.2.3 Search with unknown number of targets and erroneous observations; 2.2.4 Basic information theory search with known location probabilities; 2.3 Path planning and search over graphs; 2.3.1 General BF* and A* algorithms; 2.3.2 Real-time search and learning real-time A* algorithm; 2.3.3 Moving target search and the fringe-retrieving A* algorithm; 2.4 Summary; References; Chapter 3 Models of search and decision making; 3.1 Model of search based on MDP; 3.1.1 General definitions.
- 3.1.2 Search with probabilistic and informational decision rules3.2 Partially observable MDP model and dynamic programming approach; 3.2.1 MDP with uncertain observations; 3.2.2 Simple Pollock model of search; 3.2.3 Ross model with single-point observations; 3.3 Models of moving target search with constrained paths; 3.3.1 Eagle model with finite and infinite horizons; 3.3.2 Branch-and-bound procedure of constrained search with single searcher; 3.3.3 Constrained path search with multiple searchers; 3.4 Game theory models of search; 3.4.1 Game theory model of search and screening.
- 3.4.2 Probabilistic pursuit-evasion games3.4.3 Pursuit-evasion games on graphs; 3.5 Summary; References; Chapter 4 Methods of information theory search; 4.1 Entropy and informational distances between partitions; 4.2 Static target search: Informational LRTA* algorithm; 4.2.1 Informational LRTA* algorithm and its properties; 4.2.2 Group-testing search using the ILRTA* algorithm; 4.2.3 Search by the ILRTA* algorithm with multiple searchers; 4.3 Moving target search: Informational moving target search algorithm; 4.3.1 The informational MTS algorithm and its properties.
- 4.3.2 Simple search using the IMTS algorithm4.3.3 Dependence of the IMTS algorithm's actions on the target's movement; 4.4 Remarks on programming of the ILRTA* and IMTS algorithms; 4.4.1 Data structures; 4.4.2 Operations and algorithms; 4.5 Summary; References; Chapter 5 Applications and perspectives; 5.1 Creating classification trees by using the recursive ILRTA* algorithm; 5.1.1 Recursive ILRTA* algorithm; 5.1.2 Recursive ILRTA* with weighted distances and simulation results; 5.2 Informational search and screening algorithm with single and multiple searchers.