An approach to credit assignment in classifier systems
Thomas H. Westerdale · Complexity · 1998
We present a conceptual framework within which we can analyze simple reward schemes for classifier systems. The framework consists of a set of classifiers, a learning mechanism, and a finite automaton environment that outputs payoff. We find that many reward schemes have negative biases that degrade system performance. We analyze bucket brigade schemes, which are subgoal reward schemes, and profit sharing schemes, which aren't. By contrasting these schemes, we hope to better understand the place of subgoal reward in learning and evolution. © 1998 John Wiley & Sons, Inc.