Anticipation (artificial intelligence)

In artificial intelligence (AI), anticipation is the concept of an agent making decisions based on predictions, expectations, or beliefs about the future. It is widely considered that anticipation is a vital component of complex natural cognitive systems. As a branch of AI, anticipatory systems is a specialization still echoing the debates from the 1980s about the necessity for AI for an internal model.

Reaction, proaction and anticipation

Elementary forms of artificial intelligence can be constructed using a policy based on simple if-then rules. An example of such a system would be an agent following the rules

If it rains outside,
  take the umbrella.
Otherwise
  leave the umbrella home

A system such as the one defined above might be viewed as inherently reactive because the decision making is based on the current state of the environment with no explicit regard to the future. An agent employing anticipation would try to predict the future state of the environment (weather in this case) 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 appear more proactive, because they explicitly take into account possible future events. Notice though that in terms of representation and reasoning, these two rule sets are identical, both behave in response to existing conditions. Note too that both...
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