Modern simulations and games have limited capabilities for simulated characters to interact with each other and with humans in rich, meaningful ways. Although significant achievements have been made in developing human behavior models (HBMs) that are able to control a single simulated entity (or a single group of simulated entities), a limiting factor is the inability of HBMs developed by different groups to interact with each other. We present an architecture and multi-level message framework for enabling HBMs to communicate with each other about their actions and their intents, and describe the results of our crowd control demonstration system which applied it to allow three distinct HBMs to interoperate within a single training-oriented simulation. Our hope is that this will encourage the development of standards for interoperability among HBMs which will lead to the development of richer training and analysis simulations.