HIERARCHICAL DISCRETIZED PURSUIT
Athanasios V. Vasilakos, Georgios I. Papadimitriou, Constantinos T. Paximadis · 1991
In this paper we present a new absorbing multiaction learning automaton which we prove to be epsilon-optimal. The proposed automaton (named HDPNRI) is a hierarchical discretized nonlinear one which utilizes a new pursuit learning algorithm. The HDPNRI automaton has the best performance (speed of convergence, CPU time and accuracy) among all the absorbing learning automata reported in the literature. Extensive simulation results indicate the superiority of HDPNRI's performance.