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008			220113s2021 sz | s |||| 0|eng d
020			_a9783030608989
024	7		_a10.1007/978-3-030-60898-9 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQ337.3 _b2021 EB
245	0	0	_aShepherding UxVs for Human-Swarm Teaming : _bAn Artificial Intelligence Approach to Unmanned X Vehicles _cedited by Hussein A. Abbass, Robert A. Hunjet
250			_aFirst edition 2021
264		1	_aCham _bSpringer International Publishing _c2021
300			_a1 recurso en línea (XX, 330 páginas) _b 88 ilustraciones, 44 ilustraciones a color
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_aarchivo de texto _bPDF
490	0		_aUnmanned System Technologies _x2523-3742
490	0		_aEngineering (SpringerNature-11647)
490	0		_aEngineering (R0) (SpringerNature-43712)
505	0		_aIntroduction -- Introduction to Shepherding -- Introduction to Human-Swarm Teaming -- Swarm Shepherding on Ground -- Swarm Shepherding in Air -- Swarm Shepherding in Air Traffic Control -- Swarm Shepherding in Sea -- Genetic Algorithms for Optimizing Swarm Shepherding -- Reinforcement Learning for Swarm Shepherding -- Learning Classifier Systems for Swarm Shepherding -- Transparent Learning for Swarm Shepherding -- Ontology-guided Learning for Swarm Shepherding -- Mission Planning for Swarm Shepherding -- Real-Time Human Performance Analysis for Human-Swarm Teaming -- Trust for Human-Swarm Teaming -- Machine Education of Smart Shepherds -- The effect of communication range limits on shepherding performance -- Controlling the controllers: the multi shepherd swarm control problem -- Conclusion.
520	3		_aThis book draws inspiration from natural shepherding, whereby a farmer utilizes sheepdogs to herd sheep, to inspire a scalable and inherently human friendly approach to swarm control. The book discusses advanced artificial intelligence (AI) approaches needed to design smart robotic shepherding agents capable of controlling biological swarms or robotic swarms of unmanned vehicles. These smart shepherding agents are described with the techniques applicable to the control of Unmanned X Vehicles (UxVs) including air (unmanned aerial vehicles or UAVs), ground (unmanned ground vehicles or UGVs), underwater (unmanned underwater vehicles or UUVs), and on the surface of water (unmanned surface vehicles or USVs). This book proposes how smart 'shepherds' could be designed and used to guide a swarm of UxVs to achieve a goal while ameliorating typical communication bandwidth issues that arise in the control of multi agent systems. The book covers a wide range of topics ranging from the design of deep reinforcement learning models for shepherding a swarm, transparency in swarm guidance, and ontology-guided learning, to the design of smart swarm guidance methods for shepherding with UGVs and UAVs. The book extends the discussion to human-swarm teaming by looking into the real-time analysis of human data during human-swarm interaction, the concept of trust for human-swarm teaming, and the design of activity recognition systems for shepherding. Presents a comprehensive look at human-swarm teaming; Tackles artificial intelligence techniques for swarm guidance; Provides artificial intelligence techniques for real-time human performance analysis.
988			_aSpringer_Engineering_2021
650		7	_2embne _9667894 _aSistemas multiagente
700	1		_aAbbass, Hussein A. _eeditor literario _936963
700	1		_aHunjet, Robert A. _eeditor literario _9680547
776	0	8	_iPrinted edition: _z9783030608972
776	0	8	_iPrinted edition: _z9783030608996
776	0	8	_iPrinted edition: _z9783030609009
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-60898-9 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b01/2022 _dz _eIG _zSI