  This work introduces SwarmRL, a Python package designed to study intelligent
active particles. SwarmRL provides an easy-to-use interface for developing
models to control microscopic colloids using classical control and deep
reinforcement learning approaches. These models may be deployed in simulations
or real-world environments under a common framework. We explain the structure
of the software and its key features and demonstrate how it can be used to
accelerate research. With SwarmRL, we aim to streamline research into
micro-robotic control while bridging the gap between experimental and
simulation-driven sciences. SwarmRL is available open-source on GitHub at
https://github.com/SwarmRL/SwarmRL.
