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.


Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Not the answer you're looking for? Browse other questions tagged or ask your own question.