There is a one nice way around the intractable problems of maintaining a huge model of the world: don't. Rodney Brooks' famous saying: "the world is its own best representation." And it isn't necessary or usually even helpful to translate all incoming data into some propositional model. Again: what is your use case? If you are just trying to satisfy some essentialist intuition of what it means to be intelligent and what 'must be' inside minds, then you will be lucky to ever get anything meaningful done.
If you want to write an agent to do something without ongoing guidance, and you have not thought out the task from the beginning to get a specific algorithm, do not start by making a monolithic program that makes lots of vague high-level decisions like "how much reality" based on abstruse constructions of data. Start with the data which is always available, processed minimally, and see how little you can do. Implement walking before you implement steering and implement steering before you implement path-finding.