Learn Omega-matic: System Description

Mateja Jamnik, Manfred Kerber, Martin Pollet

Abstract: We devised a framework within which a proof planning [1] system can learn frequently occurring patterns of reasoning automatically from a number of typical examples, and then use them in proving new theorems [2]. The availability of such patterns, captured as proof methods in a proof planning system, reduces search and proof length. We implemented this learning framework for the proof planner Ωmega [3], and present it in this paper — we call our system LearnΩmatic. The entire process of learning and using new proof methods in LearnΩmatic onsists of the following steps: