SYSTEM AND METHOD FOR TYPE 2 KASER (KNOWLEDGE AMPLIFICATION BY STRUCTURED EXPERT RANDOMIZATION)

A KASER (Knowledge Amplification by Structured Expert Randomization) engine reaches conclusions in a semantic format or which take the form of a series of rules. The conclusions are parsed into an array structure having a hierarchical order of validity. A set of inserted rules is received as an initial rules array and are configured so that an antecedent comprises a non-empty, sorted set and a consequent comprises a non-empty sequence. A hierarchy of validity for the rules is determined and the rules are sorted according to the hierarchy. At least one rule set which optimizes the selection of rules is determined, with the rule set meeting predetermined validity requirements, and the rules are ordered in an order of validity, such as an order based on a maximal length antecedent set as a highest rank.