  Active matter, as other types of self-organizing systems, relies on the
take-up of energy that can be used for different actions, such as active motion
or structure formation. Here we provide an agent-based framework to model these
processes at different levels of organization, physical, biological and social,
using the same dynamic approach. Driving variables describe the take-up,
storage and conversion of energy, whereas driven variables describe the energy
consuming activities. The stochastic dynamics of both types of variables follow
a modified Langevin equation. Additional non-linear functions allow to encode
system-specific hypotheses about the relation between driving and driven
variables. To demonstrate the applicability of this framework, we recast a
number of existing models of Brownian agents and Active Brownian Particles.
Specifically, active motion, clustering and self-wiring of networks based on
chemotactic interactions, online communication and polarization of opinions
based on emotional influence are discussed. The framework allows to obtain
critical parameters for active motion and the emergence of collective
phenomena. This highlights the role of energy take-up and dissipation in
obtaining different dynamic regimes.
