Anticipation (artificial intelligence)
In artificial intelligence, anticipation occurs when an agent makes decisions based on its explicit beliefs about the future. More broadly, "anticipation" can also refer to the ability to act in appropriate ways that take future events into account, without necessarily explicitly possessing a model of the future events.
The concept stays in contrast to the reactive paradigm, which is not able to predict future system states.
In AI
An agent employing anticipation would try to predict the future state of the environment and make use of the predictions in the decision making. For example,If the sky is cloudy and the air pressure is low,
it will probably rain soon
so take the umbrella with you.
Otherwise
leave the umbrella home.
These rules explicitly take into account possible future events.
In 1985, Robert Rosen defined an anticipatory system as follows:
To some extent, Rosen's definition of anticipation applies to any system incorporating machine learning. At issue is how much of a system's behaviour should or indeed can be determined by reasoning over dedicated representations, how much by on-line planning, and how much must be provided by the system's designers.