Establishing Logical Rules from Empirical Data

We review a method of generating logical rules, or axioms, from empirical data. This method, using closed set properties of formal concept analysis, has been previously described and tested on rather large sets of deterministic data. The contribution of this paper is a completely new extension of this method to create implications involving numeric inequalities. 1 Rule Based Systems Russell and Norvig assert that “the representation of knowledge, and reasoning processes that bring knowledge to life, are central to the entire field of artificial intelligence” (p. 194 [22]). Reasoning in turn is based on logical implication which enables both forward and backward chaining techniques. In this paper we introduce a somewhat unusual representation of both existential knowledge and reasoning rules, that is logical implications, about a closed world of which we have gained some knowledge. We assume a classical, deterministic world in which inference steps, such as modus ponens, are vali...

• Type: Conference
• Year: 2007
• Where: ICTAI
• Authors: John L. Pfaltz
• Keywords: Artificial Intelligence, Closed Set Properties, ICTAI 2007, Logical Implication, Logical Rules