Ada^livft or "ieuming" ayatemB can automatlc-illy modify their ovm structures to OY^imizt performance based on past experiences. The system desiwier "teaches" by shoving the system examples of l..puc slyiilo or pattemp and simultaneously what he would like the output to be for each input. The cyBtem In turn organizes Itself to comply as wall as possible with the wishes of the designer. An adaptive pattern classification machine (called "Adallne", for adaptive linear) hac been devised to illustrate adaptive behavior and artificial learning. During a training phase, crude geometric patteri.3 arp fed to the machine by setting the toggle swJt.hes in a Vx 1 * input array. Setting another toss^e switch tells the machine whether the desired output for the particular input pattern is +1 or-1. All input patterns are classified into two categories. The system learns a little from each pattern and accordingly experiences a design change. After training, the machine can be used to classify the original patterns and noisy (distorted) versionn of these patterns.

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