TY - BOOK ID - 14233107 TI - Tracking and Mapping of Spatiotemporal Quantities Using Unicellular Swarm Intelligence : Visualisation of Invisible Hazardous Substances Using Unicellular Swarm Intelligence PY - 2016 SN - 3319274236 3319274252 PB - Cham : Springer International Publishing : Imprint: Springer, DB - UniCat KW - Mechanical Engineering - General KW - Mechanical Engineering KW - Engineering & Applied Sciences KW - Swarm intelligence. KW - Multiagent systems. KW - Agent-based model (Computer software) KW - MASs (Multiagent systems) KW - Multi-agent systems KW - Systems, Multiagent KW - Collective intelligence KW - Intelligent agents (Computer software) KW - Cellular automata KW - Distributed artificial intelligence KW - Engineering. KW - Biotechnology. KW - Microbiology. KW - Statistical physics. KW - Robotics and Automation. KW - Complexity. KW - Environmental Engineering/Biotechnology. KW - Complex Systems. KW - Statistical Physics and Dynamical Systems. KW - Physics KW - Mathematical statistics KW - Microbial biology KW - Biology KW - Microorganisms KW - Chemical engineering KW - Genetic engineering KW - Construction KW - Industrial arts KW - Technology KW - Statistical methods KW - Robotics. KW - Automation. KW - Computational complexity. KW - Environmental engineering. KW - Dynamical systems. KW - Dynamical systems KW - Kinetics KW - Mathematics KW - Mechanics, Analytic KW - Force and energy KW - Mechanics KW - Statics KW - Environmental control KW - Environmental effects KW - Environmental stresses KW - Engineering KW - Environmental health KW - Environmental protection KW - Pollution KW - Sustainable engineering KW - Complexity, Computational KW - Electronic data processing KW - Machine theory KW - Automatic factories KW - Automatic production KW - Computer control KW - Engineering cybernetics KW - Factories KW - Industrial engineering KW - Mechanization KW - Assembly-line methods KW - Automatic control KW - Automatic machinery KW - CAD/CAM systems KW - Robotics KW - Automation KW - Dynamics. UR - https://www.unicat.be/uniCat?func=search&query=sysid:14233107 AB - The book discusses new algorithms capable of searching for, tracking, mapping and providing a visualization of invisible substances. It reports on the realization of a bacterium-inspired robotic controller that can be used by an agent to search for any environmental spatial function such as temperature or pollution. Using the parameters of a mathematical model, the book shows that it is possible to control the exploration, exploitation and sensitivity of the agent. This feature sets the work apart from the usual method of applying the bacterium behavior to robotic agents. The book also discusses how a computationally tractable multi-agent robotic controller was developed and used to track as well as provide a visual map of a spatio-temporal distribution of a substance. On the one hand, this book provides biologists and ecologists with a basis to perform simulations related to how individual organisms respond to spatio-temporal factors in their environment as well as predict and analyze the behavior of organisms at a population level. On the other hand, it offers robotic engineers practical and fresh insights into the development of computationally tractable algorithms for spatial exploratory and mapping robots. It also allows a more general audience to gain an understanding of the design of computational intelligence algorithms for autonomous physical systems. ER -