Related references
Note: Only part of the references are listed.Survival strategies of artificial active agents
Luigi Zanovello et al.
SCIENTIFIC REPORTS (2023)
A machine learning approach to discover migration modes and transition dynamics of heterogeneous dendritic cells
Taegeun Song et al.
FRONTIERS IN IMMUNOLOGY (2023)
Analytic Solution of an Active Brownian Particle in a Harmonic Well
Michele Caraglio et al.
PHYSICAL REVIEW LETTERS (2022)
Active particles using reinforcement learning to navigate in complex motility landscapes
Paul A. Monderkamp et al.
MACHINE LEARNING-SCIENCE AND TECHNOLOGY (2022)
Target Search of Active Agents Crossing High Energy Barriers
Luigi Zanovello et al.
PHYSICAL REVIEW LETTERS (2021)
Microswimmers learning chemotaxis with genetic algorithms
Benedikt Hartl et al.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2021)
Reinforcement learning with artificial microswimmers
S. Muinos-Landin et al.
SCIENCE ROBOTICS (2021)
NeuroEvolution of augmenting topologies for solving a two-stage hybrid flow shop scheduling problem: A comparison of different solution strategies
Sebastian Lang et al.
EXPERT SYSTEMS WITH APPLICATIONS (2021)
Optimal navigation strategy of active Brownian particles in target-search problems
Luigi Zanovello et al.
JOURNAL OF CHEMICAL PHYSICS (2021)
Self-learning how to swim at low Reynolds number
Alan Cheng Hou Tsang et al.
PHYSICAL REVIEW FLUIDS (2020)
Active Brownian motion in two dimensions under stochastic resetting
Vijay Kumar et al.
PHYSICAL REVIEW E (2020)
Machine learning strategies for path-planning microswimmers in turbulent flows
Jaya Kumar Alageshan et al.
PHYSICAL REVIEW E (2020)
Zermelo's problem: Optimal point-to-point navigation in 2D turbulent flows using reinforcement learning
L. Biferale et al.
CHAOS (2019)
Swimming with magnets: From biological organisms to synthetic devices
Stefan Klumpp et al.
PHYSICS REPORTS-REVIEW SECTION OF PHYSICS LETTERS (2019)
Optimal steering of a smart active particle
E. Schneider et al.
EPL (2019)
The statistical physics of active matter: From self-catalytic colloids to living cells
Etienne Fodor et al.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS (2018)
Glider soaring via reinforcement learning in the field
Gautam Reddy et al.
NATURE (2018)
Smart inertial particles
Simona Colabrese et al.
PHYSICAL REVIEW FLUIDS (2018)
Intelligent Micro/nanomotors with Taxis
Ming You et al.
ACCOUNTS OF CHEMICAL RESEARCH (2018)
Finding efficient swimming strategies in a three-dimensional chaotic flow by reinforcement learning
K. Gustavsson et al.
EUROPEAN PHYSICAL JOURNAL E (2017)
Flow Navigation by Smart Microswimmers via Reinforcement Learning
Simona Colabrese et al.
PHYSICAL REVIEW LETTERS (2017)
The topography of the environment alters the optimal search strategy for active particles
Giorgio Volpe et al.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2017)
Cellular Cargo Delivery: Toward Assisted Fertilization by Sperm-Carrying Micromotors
Mariana Medina-Sanchez et al.
NANO LETTERS (2016)
Multifunctional aptamer-based nanoparticles for targeted drug delivery to circumvent cancer resistance
Juan Liu et al.
BIOMATERIALS (2016)
Synthetic biology to access and expand nature's chemical diversity
Michael J. Smanski et al.
NATURE REVIEWS MICROBIOLOGY (2016)
How Far from Equilibrium Is Active Matter?
Etienne Fodor et al.
PHYSICAL REVIEW LETTERS (2016)
Learning to soar in turbulent environments
Gautam Reddy et al.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2016)
Active Particles in Complex and Crowded Environments
Clemens Bechinger et al.
REVIEWS OF MODERN PHYSICS (2016)
Neutrophil migration in infection and wound repair: going forward in reverse
Sofia de Oliveira et al.
NATURE REVIEWS IMMUNOLOGY (2016)
Physics of microswimmers-single particle motion and collective behavior: a review
J. Elgeti et al.
REPORTS ON PROGRESS IN PHYSICS (2015)
The Environmental Impact of Micro/Nanomachines. A Review
Wei Gao et al.
ACS NANO (2014)
Multiple-robot drug delivery strategy through coordinated teams of microswimmers
U. Kei Cheang et al.
APPLIED PHYSICS LETTERS (2014)
First Order Transition for the Optimal Search Time of Levy Flights with Resetting
Lukasz Kusmierz et al.
PHYSICAL REVIEW LETTERS (2014)
Biocompatibility of engineered nanoparticles for drug delivery
Sheva Naahidi et al.
JOURNAL OF CONTROLLED RELEASE (2013)
Intelligent, self-powered, drug delivery systems
Debabrata Patra et al.
NANOSCALE (2013)
Hydrodynamics of soft active matter
M. C. Marchetti et al.
REVIEWS OF MODERN PHYSICS (2013)
Diffusive transport without detailed balance in motile bacteria: does microbiology need statistical physics?
M. E. Cates
REPORTS ON PROGRESS IN PHYSICS (2012)
Projective simulation for artificial intelligence
Hans J. Briegel et al.
SCIENTIFIC REPORTS (2012)
Diffusion with Stochastic Resetting
Martin R. Evans et al.
PHYSICAL REVIEW LETTERS (2011)
Intermittent search strategies
O. Benichou et al.
REVIEWS OF MODERN PHYSICS (2011)
Biomechanical analysis of gait adaptation in the nematode Caenorhabditis elegans
Christopher Fang-Yen et al.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2010)
Chance and strategy in search processes
M. Moreau et al.
JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT (2009)
Robustness of optimal intermittent search strategies in one, two, and three dimensions
C. Loverdo et al.
PHYSICAL REVIEW E (2009)
Undulatory Swimming in Sand: Subsurface Locomotion of the Sandfish Lizard
Ryan D. Maladen et al.
SCIENCE (2009)
Lévy flights and superdiffusion in the context of biological encounters and random searches
G.M. Viswanathan et al.
Physics of Life Reviews (2008)
Two-dimensional intermittent search processes:: An alternative to Levy flight strategies
O. Benichou et al.
PHYSICAL REVIEW E (2006)
Sperm guidance in mammals - an unpaved road to the egg
M Eisenbach et al.
NATURE REVIEWS MOLECULAR CELL BIOLOGY (2006)
Optimal search strategies for hidden targets -: art. no. 198101
O Bénichou et al.
PHYSICAL REVIEW LETTERS (2005)
How do site-specific DNA-binding proteins find their targets?
SE Halford et al.
NUCLEIC ACIDS RESEARCH (2004)
Evolving neural networks through augmenting topologies
KO Stanley et al.
EVOLUTIONARY COMPUTATION (2002)