Statistical Features in Learning
  We study some features of learning models based on "delayed" and undifferentiated reinforcement and realized by simple algorithms which may be considered of a very elementary nature. We show that a modification of the Hebb-rule works well for this problem in a neural network realization and study numerically its convergence properties. An illustration for a more "concrete" situation is provided. 
Ion-Olimpiu Stamatescu (Inst. Theor. Physik, Heidelberg, and FEST,   Heidelberg, Germany)