Reinforcement learning with artificial microswimmers
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F21%3A10438887" target="_blank" >RIV/00216208:11320/21:10438887 - isvavai.cz</a>
Result on the web
<a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=ykMGMBiOer" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=ykMGMBiOer</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1126/scirobotics.abd9285" target="_blank" >10.1126/scirobotics.abd9285</a>
Alternative languages
Result language
angličtina
Original language name
Reinforcement learning with artificial microswimmers
Original language description
Artificial microswimmers that can replicate the complex behavior of active matter are often designed to mimic the self-propulsion of microscopic living organisms. However, compared with their living counterparts, artificial microswimmers have a limited ability to adapt to environmental signals or to retain a physical memory to yield optimized emergent behavior. Different from macroscopic living systems and robots, both microscopic living organisms and artificial microswimmers are subject to Brownian motion, which randomizes their position and propulsion direction. Here, we combine real-world artificial active particles with machine learning algorithms to explore their adaptive behavior in a noisy environment with reinforcement learning. We use a real-time control of self-thermophoretic active particles to demonstrate the solution of a simple standard navigation problem under the inevitable influence of Brownian motion at these length scales. We show that, with external control, collective learning is possible. Concerning the learning under noise, we find that noise decreases the learning speed, modifies the optimal behavior, and also increases the strength of the decisions made. As a consequence of time delay in the feedback loop controlling the particles, an optimum velocity, reminiscent of optimal run-and-tumble times of bacteria, is found for the system, which is conjectured to be a universal property of systems exhibiting delayed response in a noisy environment.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10300 - Physical sciences
Result continuities
Project
<a href="/en/project/GC20-02955J" target="_blank" >GC20-02955J: Dynamics and thermodynamics in artificial and natural active systems with delay</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Science Robotics
ISSN
2470-9476
e-ISSN
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Volume of the periodical
6
Issue of the periodical within the volume
52
Country of publishing house
US - UNITED STATES
Number of pages
8
Pages from-to
eabd9285
UT code for WoS article
000649297100003
EID of the result in the Scopus database
2-s2.0-85104588219