PostHeaderIcon Learning By Parameter Adjustment

What is Learning by parameter adjustment?

Here the learning system relies on evaluation procedure that combines information from several sources into a single summary static. For example, the factors such as demand and production capacity may be combined into a single score to indicate the chance for increase of production. But it is difficult to know a priori how much weight should be attached to each factor.

The correct weight can be found by taking some estimate of the correct settings and then allow the program modify its settings based on its experience. This type of learning systems is useful when little knowledge is available. In game programs, for example, the factors such as piece advantage and mobility are combined into a single score to decide whether a particular board position is desirable. This single score is nothing but a knowledge which the program gathered by means of calculation.

NEXT Learning With Macro Operators