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?


1 Answer 1


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.


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