Physicomimetics

Physics-Based Swarm Intelligence

Inbunden, Engelska, 2012

1 389 kr

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The editors consolidated over a decade of work on swarm intelligence and swarm robotics, organizing the book into 19 chapters as follows. finally, Part V shows that physicomimetics can be used for function optimization, moving the reader from issues of swarm robotics to swarm intelligence.

Produktinformation

Utgivningsdatum2012-01-05
Mått155 x 235 x 40 mm
Vikt1 128 g
FormatInbunden
SpråkEngelska
Antal sidor646
Upplaga2012
FörlagSpringer-Verlag Berlin and Heidelberg GmbH & Co. KG
ISBN9783642228032

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Dr. William Spears is the CEO of Swarmotics LLC, a company that provides consulting expertise in distributed agents, sensing networks, artificial intelligence, machine learning, optimization, and swarm robotics; he was formerly a professor in the Dept. of Computer Science at the University of Wyoming, Laramie. Dr. Diana Spears was a professor in the Dept. of Computer Science at the University of Wyoming, Laramie, and is currently a director of Swarmotics, LLC.

Part I - Introduction Chap. 1 - Nature Is Lazy Chap. 2 - NetLogo and Physics Chap. 3 - NetLogo and Physicomimetics Chap. 4 - Pushing the Envelope Part II - Robotic Swarm Applications Chap. 5 - Local Oriented Potential Fields: Self-deployment and Coordination of an Assembling Swarm of Robots Chap. 6 - Physicomimetics for Distributed Control of Mobile Aquatic Sensor Networks in Bioluminescent Environments Chap. 7 - Gas-Mimetic Swarms for Surveillance and Obstacle Avoidance Chap. 8 - A Multirobot Chemical Source Localization Strategy Based on Fluid Physics: Theoretical Principles Chap. 9 - A Multirrobot Chemical Source Localization Strategy Based on Fluid Physics: Experimental Results Part III - Physicomimetics on Hardware Robots Chap. 10 - What Is a Maxelbot? Chap. 11 - Uniform Coverage Chap. 12 - Chain Formations Chap. 13 - Physicomimetic Motion Control of Physically Constrained Agents Part IV - Prediction, Adaptation, and Swarm Engineering Chap. 14 - Adaptive Learning by Robot Swarms in Unfamiliar Environments Chap. 15 - A Statistical Framework for Estimating the Success Rate of Liquid-Mimetic Swarms Chap. 16 - Physicomimetic Swarm Design Considerations: Modularity, Scalability, Heterogeneity, and the Prediction Versus Control Dilemma Chap. 17 - Using Swarm Engineering to Design Physicomimetic Swarms Part V - Function Optimization Chap. 18 - Artificial Physics Optimization Algorithm for Global Optimization Chap. 19 - Artificial Physics for Noisy Nonstationary Environments App. A - Anomalous Behavior of the Random Number Generator Index References