Open AccessEmergent Intelligence and Distributed Stochastic Optimization
Author(s) -
Oleg Granichin,
Olga Granichina,
Victoria Erofeeva,
A.V. Leonova,
Alexander Senov
Publication year - 2022
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1215/1/012001
Subject(s) - computer science , simple (philosophy) , property (philosophy) , natural (archaeology) , noise (video) , distributed computing , artificial intelligence , philosophy , archaeology , epistemology , image (mathematics) , history
Emergent intelligence is a property of a system of elements that is not inherent in each element individually. This behavior is based on local communications. This behavior helps to adapt to emerging uncertainties and achieve a global goal. This behavior exists in the natural world. A simplified example of emergent intelligence from the natural world is given. The repetition of natural behavior with the help of simple technical devices, which are limited in resources and cheap in construction, and the use of multi-agent approaches is considered. Distributed algorithms using local communications are considered. Such algorithms are more robust to noise.