Enabling Intelligence With Temporal World Models

A system for storing knowledge along with the ability to query it, which together we call a world model, provides a central source of relevant information to the various processes that constitute an autonomous agent. We outline the development of a world model that supports ontologies to describe the world, and provides interfaces for processes to populate and query the system, including queries over time. The world model is implemented as a tuple store with structural subsumption query support. We evaluate its effectiveness on an embodied system, and show that it can answer spatiotemporal queries about objects observed in the environment.