| Anticipation (artificial Intelligence) |
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REACTION AND PROACTION Elementary forms of artificial intelligence can be constructed using a policy based on simple if-then rules. An example of a such 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 is inherently reactive because the decision making is based solely on the current state of the environment with no 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 predicions in the decision making. For example If the sky is cloudy and the air preassure is low, it will probably rain soon so take the umbrella with you. Otherwise leave the umbrella home. The key component to anticipation is the existence of an inner model of the environment of the anticipatory system (sometimes including the system itself). Robert Rosen defined an anticipatory system as follows A system containing a predictive model of itself and/or its environment, which allows it to change state at an instant in accord with the model's predictions pertaining to a latter instant. REFERENCES
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