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Non-axiomatic reasoning system
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Non-axiomatic logic, or non-axiomatic reasoning system, is a branch of computer science that applies logic for the creation of general-purpose artificial intelligence systems. This is done by formulating fundamental regularity of human thinking at a general level. Also known as NAL, it differs from ordinary logic systems in all of its major aspects, including: * subject predicate sentences, experience-grounded semantics, syllogistic inference rules. The difference is significant enough for some logicians to classify it as "logic" per se. One of the thought leaders in this field is Pei Wang, who published a book on this entitled "Non-Axiomatic Logic: A Model of Intelligent Reasoning" (2013). Reasoning systems At a conceptual level, reasoning systems have five major components: # Grammar rules # Inference rules # Semantic rules # Control mechanism # Memory structure Components 1 to 3 are the "logic" infused into the reasoning system. Non-axiomatic logic (NAL) is in contrast to axiomatic logic in the sense that NAL is fitted for realistic situations while axiomatic logic is good for idealistic situations. Since knowledge can be challenged with new evidence, there is no axiom in a given system that is "guaranteed truth". 
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