The role of logic in AGI systems: Towards a lingua franca for general intelligence

Abstract

Systems for general intelligence require a significant potential to model a variety of different cognitive abilities. It is often claimed that logic-based systems - although rather successful for modeling specialized tasks - lack the ability to be useful as a universal modeling framework due to the fact that particular logics can often be used only for special purposes (and do not cover the whole breadth of reasoning abilities) and show significant weaknesses for tasks like learning, pattern matching, or controlling behavior. This paper argues against this thesis by exemplifying that logic-based frameworks can be used to integrate different reasoning types and can function as a coding scheme for the integration of symbolic and subsymbolic approaches. In particular, AGI systems can be based on logic frameworks.