SOME NEW APPROACHES TO MACHINE LEARNING

Five different but interrelated models of learning have been established within a complex computer program. These models incorporate mechanisms that optimize response patterns on algorithmic and heuristic bases; make abstractions at different levels; produce value judgements; recognize, modify, store, and retrieve geometrical patterns; and exhibit, in general, many aspects of intelligent behavior. Both the teacher and the learner are simulated in the machine. In one model, the program follows a qualitatively new kind of learning process in generating its own strategy and improving it on the basis of experience. The method enables the learner to exceed the playing quality of the teacher. It is suggested that the methods and techniques employed in the project may be useful in mechanizing some problem-solving activities that can be reduced to pattern recognition, such as meteorological forecasting, medical diagnosis, traffic control, and so on. No deliberate attempt has been made to imitate humans. Copyright © 1969 by The Institute of Electrical and Electronics Engineers, Inc.