Training the human adaptive controller

The training of human operators for skilled tasks may be regarded as the synthesis of a specific controller from a general-purpose adaptive device, by influencing its adaption through selection and variation of the learning environment. Selection of environments to maximise the rate of learning is itself a control problem, and an automatic feedback training system is proposed which feeds back information about the operator´s performance to control the parameters of his environment. The stability and performance of the trainer have been investigated both theoretically and experimentally, and its utility has been tested in a fairly realistic training situation using as trainees both human operators and computer-simulated learning machines.