Infobody Structures for Logical Artificial Intelligence with Database Implementation

The purpose of this paper is to explore the applications of infobody concepts, infobody structures and infobody charts to Artificial Intelligence (AI), specifically, Logical Artificial Intelligence (LAI). It is also trying to explore a new way to resolve some logical issues in current Artificial Intelligence studies with ChatGPT such as answering reasoning questions in family relations. For this purpose, detailed family relations are discussed based on relation theory. Some new concepts such as primary relations, reversed relations and derived relations for family relations are introduced. Also, a relational database is introduced to implement these family relations and the relationships between these family relations, and make them calculatable with SQL. Each SQL query becomes an infobody processor and together with the input and output infobodies compose a unit infobody structure. Multiple unit structures compose an answer structure to answer a specific question in family relations. A specific unit structure can join multiple answer structures to answer multiple questions. A processor with related input infobodies contains all detailed information for reasoning to a specific outp