AD-CASPAR: Abductive-Deductive Cognitive Architecture based on Natural language and first order logic Reasoning

In this paper, a Cognitive Architecture leveraging Natural Language Processing and First Order Logic Inference is presented, making usage of different kinds of knowledge bases interacting one another. Such a framework is able to make reasoning on queries requiring also combinations of axioms, represented by means of a rich semantic, using Abduction as pre-stage of Deduction. As application test a Telegram chatbot system has been implemented, supported by a module which automatically transforms polar and wh-questions into one or more likely assertions, in order to infer boolean values or snipplets with variable length as factoid answer. Furthermore, such a chatbot does not need script updates or code refactory when new knowledge has to income, but just the knowledge itself in natural language.