Admiral is a package for developing agent based simulations and training them with multiagent reinforcement learning. A reinforcement learning experiment contains two main components: (1) a simulation environment and (2) learning agents, which contain policies that map observations to actions. These policies may be hard-coded by the researcher or trained by the RL algorithm. In Admiral, these two components are specified in a single Python configuration script. The components can be defined in-script or imported as modules.