In agent-based systems, agents can team in different combinations to cooperatively solve problems. Teaming, however, requires that agents understand each other and commit to concerted actions. In open, evolving networked systems, universal understanding and commitment are unlikely; instead, agents should congregate with those agents that they can understand and with whom they have successfully teamed in the past. Agent congregations are defined by commitments to common semantics and ontologies (conceptualizations of the world). Congregating improves the efficiency of communication and the likelihood of successful teaming. It can, however, impede the formation of effective teams whose members cross congregations, because agents need to learn new ontologies and incur overhead in searching for new congregations that meet their preferences. This project investigates how agent congregations are formed and how and when they should be reformed. The research includes simulations of large communities of agents, formal models of agency, and prototype systems. Its results will help guide the development of a national computing and communication infrastructure that supports the evolving identities and interests of scientific, educational, and commercial communities, and encourages communication between different communities. http://ai.eecs.umich.edu/people/wpb/conagents/
