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Global extremum seeking by Kriging with a multi-agent system

Abstract : This paper presents a method for finding the global maximum of a spatially varying field using a multi-agent system. A surrogate model of the field is determined via Kriging (Gaussian process regression) from a set of sampling measurements collected by the agents. A criterion exploiting Kriging statistical properties is introduced for selecting new sampling points that each vehicle must rally. These new points are obtained as a compromise between improvement of the estimate of the global maximum and traveling distance. A cooperative control law is proposed to move the agents to the desired sampling positions while avoiding collisions. Simulation results show the interest of the method and how it compares with a state-of-art solution.
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Contributor : Julien Marzat <>
Submitted on : Tuesday, July 21, 2015 - 11:58:19 AM
Last modification on : Wednesday, April 8, 2020 - 3:40:53 PM
Document(s) archivé(s) le : Wednesday, April 26, 2017 - 7:33:39 AM


2015 - IFAC SYSID - Global ext...
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  • HAL Id : hal-01170131, version 2


Arthur Kahn, Julien Marzat, Hélène Piet-Lahanier, Michel Kieffer. Global extremum seeking by Kriging with a multi-agent system. 2015. ⟨hal-01170131v2⟩



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