… We illustrate the practical potential through a range of applications, from a chiral active
particle model mimicking nonidentical swimming cells to recent microroller experiments and …

… of active Brownian particles, active particles undergoing … in coupling machine-learning models
to active particles, in a quest to … -learning approach, ActiveNet, that can be trained to learn …

… With the help of a tabular Q-learning algorithm, we design a model for training a … We show
that the strategy obtained with our reinforcement learning model indeed represents an efficient …

… colloidal engines, adaptive responses of active colloids with the help of machine learning …
on modeling active matter on the particle level and not on field-based continuum modeling, …

This paper proposes a systems approach to the theory of perception and learning in
populations composed of many living entities. Starting from a phenomenological description of …

… To date, it remains an open problem to understand how well-established foraging models
such as Lévy walks or chemotaxis models would hold up when we account for key real-world …

… model-based reinforcement learning [150,151] and more importantly world models [152]
where the agents strive to learn a model (… can even be translated to learning the physics of the …

… issue: Can we identify the active species in a binary model system of active and passive …
-based machine learning approach for the identification of active particles in an active/passive …

… tools witness the interest of applied mathematicians toward modeling, qualitative analysis,
and computing of large systems of active particles viewed as living, hence complex, systems. …

… Here we develop a machine learning-based approach that … -based deep reinforcement
learning techniques and, crucially, … a universal path planner for future intelligent active particles. …