Abstract

. The problem of learning decision rules for sequential tasks is addressed, focusing on the problem of learning tactical decision rules from a simple flight simulator. The learning method relies on the notion of competition and employs genetic algorithms to search the space of decision policies. Several experiments are presented that address issues arising from differences between the simulation model on which learning occurs and the target environment on which the decision rules are ultimately tested. Key words: sequential decision rules, competition-based learning, genetic algorithms Running Head: Learning Sequential Decision Rules Machine Learning 5(4), 355-381. - 2 - 1. Introduction In response to the knowledge acquisition bottleneck associated with the design of expert systems, research in machine learning attempts to automate the knowledge acquisition process and to broaden the base of accessible sources of knowledge. The choice of an appropriate learning technique depends on ...

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