What is the difference between simple reflex and model-based agents?
What is the role of the internal state, in the case of model-based agents?
A simplex reflex agent takes actions based on current situational experiences.
For example, if you set your smart bulb to turn on at some given time, let's say at 9 pm, the bulb won't recognize how the time is longer simply because that's the rule defined it follows.
A simple reflex agent doesn't compute complex computational problems nor exhibit intelligence.
A model-based agent takes actions based on historical situational experiences. It performs actions basing on its internal state.
The internal state of the model-based agent acts as a "knowledge base", which allows actions to be performed by representing of unobserved aspects of the current state depending on percept history nor historical situational experiences.
For instance, a research-based planetary system can predict the planet's climatical conditions or weather basing on some geo-information knowledge base.