Abstract: A rule invocation mechanism in an inductive learning engine employing symbolic rules for characterizing a sequence of time-related events. The rules to be tested as hypotheses against new events in the sequence are ranked according to their information content or "quality" value. The efficiency of the rule-to-event pattern matching process for characterizing the new events is increased by not testing a hypothesis if a much better hypothesis already exists. Those hypotheses that characterize events in the sequence are tagged to the event.

Abstract: A system and method for adaptively managing the behavior of, for example, a digital data processing system, using inductive learning techniques. The new system includes a data acquistion portion that acquires event data in response to selected events. An inductive engine generates profile knowledge in response to acquired event data during a learning phase, for storage in a profile knowledge store. A profile comparator, during an operational phase, subsequent to the learning phase, performs a verification operation in connection with comparing event data to said profile knowledge stored in said profile knowledge store. A control portion enables event data acquired by said data acquisition portion to be directed to the inductive engine during a learning phase and to the profile comparator during an operational phase to thereby permit the comparator to perform a verification operation in connection with said event data acquired during the operational phase.