ADAPTIVE COMPUTING SYSTEM CAPABLE OF LEARNING AND DISCOVERY

An electronic computing system capable of learning and discovery employing a language composed of conditional statements called "classifiers" which respond to and operate fixed-length binary words called "messages". Each classifier comprises a condition part which identifies the message(s) to which the classfier responds, and an action part which specifies the content of the generated message which may, in part, be a function of one or more of the input messages. An adaptive algorithm, called the "bucket brigade algorithm", tracks the history of each classifier's performance and develops a strength value which serves as a measure of the past usefulness of that classifier in reaching a defined objective. A genetic algorithm generates new classifiers which are based on the strongest of the existing classifiers and which replace the weakest of the existing classifiers.