This research enables radically new capabilities to deploy intelligent decentralized knowledge learning and planning algorithms for teams of heterogeneous autonomous static and mobile agents. The research plan is based on the key insight that Bayesian nonparametric models (BNPM) provide a powerful framework for reasoning about objects and relations in settings in which these objects and relations are not predefined. This feature is particularly attractive for missions such as long term persistent surveillance for which it is virtually impossible to specify the size of the model and the number of variables a priori.