Toward Autonomy: Symbiotic Formal and Statistical Machine Reasoning

Abstract

Different types of machine learning, statistical types, where its knowledge in contained in set of numbers, and formal types, where its knowledge is contained in set of rules or statements, have their own strengths and weaknesses. We argue that their strengths and weaknesses are complementary, and develop a concept called Learn2Reason to harness their collective strength, without inheriting their weaknesses. The efficacy of Learn2Reason concept has been successfully demonstrated in software/binary analysis and cyber security areas. Adoption of the concept significantly improve the performance and scalability of software/binary analysis and cyber security applications and tools.