A COMPARISON OF 5 ALGORITHMS FOR THE TRAINING OF CMAC MEMORIES FOR LEARNING CONTROL-SYSTEMS

First, the cerebellar model articulation controller (CMAC), invented in the early 1970s by Albus, and the associative memory system (AMS), developed for learning control systems by H. Tolle et al. in the early 1980s, are briefly described. The underlying mathematics of the AMS learning or training algorithm is then given with a geometrical interpretation from which its convergence properties may be deduced. These are illustrated for some simple cases. The original algorithm devised by Albus is very simple to compute but is slow to converge, and the second part of the paper investigates various algorithms with improved convergence properties. One of these, the so-called "maximum error" algorithm, is particularly recommended.