Extended Event Calculus using Neutrosophic Logic: Method, Implementation, Analysis, Recent Progress and Future Directions

Abstract


 Brains do not reason as digital computers do. Computers reason in clear steps with statements that are either true or false, while humans reason with vague terms of common sense. Neutrosophy is a new branch of philosophy and machine intelligence that deals with neutralities, specifically the idea of indeterminacy that is evident and experienced in our everyday lives. Indeterminacy is interpreted as everything that falls between a concept, idea, statement, declaration, etc. and its opposite. The fundamental thesis of neutrosophy is to employ neutrosophic logic, an extension of fuzzy logic, to incorporate fuzzy truth into complex schemes of formal reasoning. Event calculus is a logical formalism used to describe and reason about events and their consequences over time. It is considered a valuable mathematical tool in the field of artificial intelligence (AI) for depicting dynamic systems where events occur and have temporal relationships with each other. However, previous studies in AI have neglected to adequately address the complexity of time. In this context, our work aims to introduce a neutrosophic event-based calculus as a logic formalism to handle situations where there is insufficient knowledge or ambiguity regarding the occurrence or consequences of certain events in a system. In particular, neutrosophic event calculus examines causality between ideas and the connection between tasks and actions in the presence of time. Due to the lack of related studies in the existing literature, we believe that our work will contribute to the field of knowledge representation by proposing an alternative to current forms of logic. We aim to demonstrate the capacity of neutrosophic event calculus in the context of knowledge representation and reasoning.