The most effective way to handle partial observability is for the agent to keep track of the part of the world it can’t see now.

Updating the internal state information as time goes by requires two kinds of knowledge to be encoded in the agent program.

First, we need some information about how the world evolves independently of the agent—for example, that an overtaking car generally will be closer behind than it was a moment ago.

Second, we need some information about how the agent’s own actions affect the world—for example, that when the agent turns the steering wheel clockwise, the car turns to the right, or that after driving for five minutes northbound on the freeway, one is usually about five miles north of where one was five minutes ago.

This knowledge about “how the world works”—whether implemented in simple Boolean circuits or in complete scientific theories—is called a model of the world.

An agent that uses such a MODEL-BASED model is called a model-based agent.