TY  - GEN
AB  - This 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.
AU  - Abbass, Hussein A.,
AU  - Hunjet, Robert A.,
CN  - Q337.3
DO  - 10.1007/978-3-030-60898-9
DO  - doi
ID  - 1435020
KW  - Swarm intelligence.
KW  - Multiagent systems.
KW  - Robots
KW  - Vehicles, Remotely piloted.
KW  - Systèmes multiagents (Intelligence artificielle)
KW  - Robots
KW  - Véhicules télécommandés.
LK  - https://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-030-60898-9
N1  - Includes index.
N2  - This 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.
SN  - 9783030608989
SN  - 3030608980
SN  - 3030608972
SN  - 9783030608972
SN  - 9783030608996
SN  - 3030608999
SN  - 9783030609009
SN  - 3030609006
T1  - Shepherding UxVs for human-swarm teaming :an artificial intelligence approach to unmanned X vehicles /
TI  - Shepherding UxVs for human-swarm teaming :an artificial intelligence approach to unmanned X vehicles /
UR  - https://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-030-60898-9
ER  -