About the Generalized Reasoning Methods and their Use in Semiotic Systems

In computational semiotics the problem is to emulate a semiosis cycle within a digital computer. This needs the construction of intelligent systems, able to perform intelligent behavior, such as sensorial perception, world modeling, value judgement and behavior generation. These intelligent systems could be generally implemented through object networks and the basic functions mentioned above could be obtained by generalization of some elementary knowledge operators. Based on the three main reasoning methods, deduction, induction and abduction, well known in the philosophy of science and used in AI systems, there were three knew knowledge operators defined: knowledge extraction, knowledge generation and knowledge generation, operators that could be viewed as generalized interpretations of the standard reasoning procedures. This paper presents these new concepts and their connection, the current understanding of generalized deduction, induction and abduction and also how these operators could serve as the building blocks of universal intelligent systems.