The Ebbinghaus Effect and the Implications of Net Learning for the Performance of Production Systems, with Some Experimental Results

This abstract will be reformatted upon A simple Ebbinghaus model suggests that the policy implications of gross learning for the performance of production systems can be misleading. The rates of net learning tend to be transitory such that knowledge accumulation and diffusion processes thereof take longer to bear fruit than conventional learning models would indicate. Consequently, continuous retooling and retraining of production systems are necessary conditions for offsetting the effects of forgetting on gross learning.