Computational semiotics

Abstract: Computational semiotics is a quite new field of research, which emerged from advanced studies on artificial intelligence and intelligent systems. It is an alternative to the mainstream approaches - those based either on cognitivism or on biologically inspired techniques. Instead, computational semiotics seeks its inspiration on semiotics, a tradition on the philosophy of mind dealing with the concepts of representation and communication from a more technical perspective. The whole story besides this new field of research is usually unknown from many researchers working on the field of intelligent systems. This story started during the 1970's, where two main precursors first published works relating semiotics to intelligent systems development, almost at the same time in Russia and in the U.S. These pioneering studies were performed by Dmitri Pospelov in Russia and Eugene Pendergraft in U.S. Despite promising research results, for diverse reasons they stayed ignored from the mainstream in artificial intelligence for about 25 years. However, around 1995 they were rediscovered, motivating the development of this new paradigm of research. The goal of this paper is to briefly review the main contributions in this area.

Abstract: This paper discusses methods for evaluating the intelligence of intelligent systems by means of computational semiotics. Instead of looking at the system as a black box and testing its behavior, the process described focuses on architectural details of structures, organizations, processes and algorithms used in the construction of the intelligent system, evaluating the impact of using these elements in the overall intelligent behavior exhibited by the system. It proposes "insider" metrics that, coupled to "outsider" metrics, will be important for the determination of general metrics for intelligence in intelligent systems.

Abstract: The aim of this paper is to introduce the theoretical foundations of an approach for intelligent systems development. Derived from semiotics, a classic discipline in human sciences, the theory developed provides a mathematical framework for the concept of knowledge and for knowledge processing. As a result, a new perspective to study and to develop intelligent systems emerges. A taxonomy of elementary types of knowledge is proposed based on the classification of types of signs in semiotics, followed by a another classification of knowledge from the point of view of application in cognitive systems. In addition, we propose the mathematical definition of objects, objects systems and objects networks, to model mathematically the different types of knowledge described. The symbiosis of such key concepts introduces a computational paradigm to develop and implement intelligent systems, called here computational semiotics.

Abstract: This paper demonstrates the importance of generalized morphisms of relations in computational semiotics. The paper starts by presenting an overview of the basic theoretical notions concerned with semiotic descriptors and relational morphisms. This is followed by a case study utilizing real life engineering data in which we show how these basic notions can be used computationally in investigation of context dependency of some linguistic engineering constructs.