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@ARTICLE{Leinen:884720,
author = {Leinen, Philipp and Esders, Malte and Schütt, Kristof T.
and Wagner, Christian and Müller, Klaus-Robert and Tautz,
F. Stefan},
title = {{A}utonomous robotic nanofabrication with reinforcement
learning},
journal = {Science advances},
volume = {6},
number = {36},
issn = {2375-2548},
address = {Washington, DC [u.a.]},
publisher = {Assoc.},
reportid = {FZJ-2020-03214},
pages = {eabb6987 -},
year = {2020},
abstract = {The ability to handle single molecules as effectively as
macroscopic building blocks would enable the construction of
complex supramolecular structures inaccessible to
self-assembly. The fundamental challenges obstructing this
goal are the uncontrolled variability and poor observability
of atomic-scale conformations. Here, we present a strategy
to work around both obstacles and demonstrate autonomous
robotic nanofabrication by manipulating single molecules.
Our approach uses reinforcement learning (RL), which finds
solution strategies even in the face of large uncertainty
and sparse feedback. We demonstrate the potential of our RL
approach by removing molecules autonomously with a scanning
probe microscope from a supramolecular structure. Our RL
agent reaches an excellent performance, enabling us to
automate a task that previously had to be performed by a
human. We anticipate that our work opens the way toward
autonomous agents for the robotic construction of functional
supramolecular structures with speed, precision, and
perseverance beyond our current capabilities.},
cin = {PGI-3},
ddc = {500},
cid = {I:(DE-Juel1)PGI-3-20110106},
pnm = {143 - Controlling Configuration-Based Phenomena (POF3-143)},
pid = {G:(DE-HGF)POF3-143},
typ = {PUB:(DE-HGF)16},
pubmed = {pmid:32917594},
UT = {WOS:000567766700027},
doi = {10.1126/sciadv.abb6987},
url = {https://juser.fz-juelich.de/record/884720},
}