On The Generalized Deduction, Induction And Abduction As The Elementary Reasoning Operators Within Computational Semiotics

We first elaborate on the definition of an elementary unit of knowledge, called here knowledge unit. Then we define three knowledge operators, knowledge extraction, knowledge generation and knowledge selection, aimed at being the elementary ways of reasoning. These are compared to the traditional deduction, induction and abduction reasoning operators, resulting in the proposal that our knowledge operators could be viewed as generalized interpretations of the standard deduction, induction and abduction reasoning procedures. We finalize by proposing them as the building blocks for universal intelligent systems.79580

Semiotic synthesis and semionic networks

ABSTRACT: In this paper we discuss a set of conceptual issues regarding the synthesis of semiotic processes within artificial systems, and its technological offspring, the semionic networks. We start by putting in context what is this thing- semiotic synthesis, and how and why it differs from semiotic analysis. We follow proposing the concept of a "semion", as both an elementary entity with semiotic processing abilities, and a container of knowledge, explaining its structure and dynamics. At the end, we address the interaction of semions within semionic networks, and its use with the purpose of building different architectures for artificial minds.

Semionics: A Proposal for the Semiotic Modeling of Organizations

ABSTRACT: In this paper, we present Semionics, a contribution to the field of Computational Semiotics, and propose its use in order to build and simulate models of organizations. Computational Semiotics refers to a research area where semiotic techniques are used in order to synthesize semiotic processes in computers and computer-based applications. Semionics is the main technology developed by our research group, based on Peircean semiotics, with the aim of providing both modeling and simulation artifacts for the design of such semiotic systems. Here we present the main backgrounds of semionics- the semionic network- what it is and how it works. Further, we show an application example of a semionic network for the modeling and simulation of a small business organization.

Towards An Introduction To Computational Semiotics

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. © 2005 IEEE.2005393398Noth, W., (1995) Handbook of Semiotics (Advances in Semiotics), , Indiana University PressPospelov, D.A., Principles of situational control (1971) Engineering Cybernetics, (2), pp. 216-222. , MoscowPospelov, D.A., (1986) Situational Control: Theory and Practice, , unpublished translation from the original in russian, edited by Nauka Publishers, MoscowPendergraft, E.P., (1964) Self-organizing Linguistic Sytems Linguistic Research Seminar, , Santa Monica, CaliforniaPendergraft, E.P., The future's voice - Intelligence based on pragmatic logic (1993) Technical Report, , Creative Intelligence Incorporated, DRAFT (FATE), Jasper, EUA, JunePospelov, D.A., Zhelezov, Zh.Y., On a class of large systems (1970) Engineering Cybernetics, (2), pp. 243-246. , MoscowPospelov, D.A., Yeimov, Ye.I., Semiotic models in planning problems of artificial intellect systems (1977) Engineering Cybernetics, (5), pp. 37-43. , MoscowOsipov, G.S., Origins of applied semiotics (2000) ECAI 2000, 14th European Conference on Artificial IntelligenceSulosky, M.F., Semiotics situational control - JSM-type reasoning and Q-analysis, intelligent systems: A semiotic perspective (1996) Proceedings of the 1996 International Multidisciplinary Conference, Vol. II: Applied Semiotics, 2. , Gaithersburg, MarylandWaterman, D.A., (1986) A Guide to Expert Systems, , Addison Wesley Publishing Company(1997) White Paper, , A Skeleton Autognome, Autognomics Corp., EUA(2001) Autognomics Technology - Brief Overview of Autognomics, , Autognomics Corp., EUAAlbus, J.S., Outline for a theory of intelligence (1991) IEEE Transactions on System, Man and Cybernetics, 21 (3). , May/JuneAlbus, J.S., Meystel, A.M., (2001) Engineering of Mind: An Introduction to the Science of Intelligent Systems, , John Wiley & SonsISBN: 0471438545Meystel, A.M., Albus, J.S., (2001) Intelligent Systems: Architecture, Design, Control, , Wiley-InterscienceISBN: 0471193747Albus, J.S., The NIST Real-time Control System (RCS): An approach to intelligent system research (1997) J. Expt. Theor. Artif. Intell, pp. 157-162Meystel, A.M., (1995) Semiotic Modeling and Situation Analysis : An Introduction, , AdRem Inc. - Bala Cynwyd, PA, USALiu, K., (2000) Semiotics in Information Systems Engineering, , Cambridge University Press, ISBN: 0521593352Liu, K., Clarke, R.J., Andersen, P.B., Stamper, R.K., (2001) Information, Organisation and Technology: Studies in Organisational Semiotics, , 2001 Kluwer Academic Publishers, ISBN: 0792372581Van Heusden, B., Jorna, R.J., Reconsidering the standard: A semiotic model of organisations Coordination and Communication Using Signs: Studies in Organisational Semiotics, 2, pp. 153-167. , Kecheng Liu, R.J. Clarke, P.B. Andersen & R.K. Stamper (Eds.). Dordrecht: Kluwer Academic PublishersGazendam, H.W.M., Semiotics, virtual organizations, and information systems (2001) Information, Organisation and Technology: Studies in Organisational Semiotics, pp. 1-48. , (2001). Kecheng Liu, Rodney J. Clarke, Peter Bøgh Andersen and Ronald K. Stamper (eds.). Boston: Kluwer Academic PublishersGazendam, H.W.M., Jorna, R.J., Semiotics, multi-agent systems and organizations (1998) Proceedings of the Joint Conference on the Science and Technology of Intelligent Systems, pp. 84-89. , (1998). September 14-17, Gaithersburg, MD, USA. Piscataway, NJ: IEEE. ISBN 0-7803-4423-3Rieger, B.B., Situations, language games, and SCIPS. Modeling semiotic cognitive information processing systems (1995) Architectures for Semiotic Modeling and Situation Analysis in Large Complex Systems (Proceedings of the 1995 ISIC-workshop, Monterey: the 10th International IEEE-symposium on Intelligent Control), pp. 130-138. , Albus, J./ Meystel, A./ Pospelov, D./ Reader, T. (eds.), Bala Cynwyd, PA. (AdRem Inc.)Rieger, B.B., Semiotics and computational linguistics. on semiotic cognitive information processing (1999) Computing with Words in Information/ Intelligent Systems I. Foundations [Studies in Fuzziness and Soft Computing], 33, pp. 93-118. , Zadeh, Lotfi A. / Kacprzyk, Janusz (eds.): Heidelberg, (Physica Verlag)Rieger, B.B., A systems theoretical view on computational semiotics. Modeling text understanding as meaning constitution by SCIPS (1998) Proceedings of the Joint IEEE Conference on the Science and Technology of Intelligent Systems (ISIC/CIRA/ISAS-98), pp. 840-845. , Piscataway, NJ (IEEE/Omnipress)Pattee, H.H., Cell psychology: An evolutionary approach to the symbol-matter problem (1982) Cognition and Brain Theory, 5 (4), pp. 325-341Joslyn, C., The semiotics of control and modeling relations in complex systems (2001) BioSystems, 60, pp. 131-148Joslyn, C., Rocha, L.M., Towards semiotic agent-based models of socio-technical organizations (2000) AI, Simulation and Planning (AIS 2000) Conference, , Tucson, Arizona, USARocha, L.M., Models of embodied, evolving, semiosis in artificial environments (1998) Proceeding of the Virtual World and Simulation Conference, pp. 233-238. , Landauer, C., Bellman, K.L. The society for Computer SimulationPerlovsky, L., Semiotics, mind and architecture of target tracker (1998) Proceedings of the IEEE ISIC/CIRA/ISAS Joint Conference, , Gaithersburg, MD. SepPerlovsky, L., (2000) Neural Networks and Intellect, , Oxford Press - ISBN 0195111621Prueitt, P.S., Is computation something new?, Intelligent systems: A semiotic perspective (1996) Proceedings of the 1996 International Multidisciplinary Conference, Vol. II: Applied Semiotics, 2. , Gaithersburg, MarylandPrueitt, P., (1999) Foundations of Knowledge Management for the 21st Century, , BCN Group Inc., EUADöben-Henisch, G., Semiotic machines - Theory, implementation, semiotic relevance (1996) 8th International Semiotic Congress of the German and the Netherlands Semiotic Societies, , Amsterdam, AugustDöben-Henisch, G., Erasmus, L., Hasebrook, J., Knowledge robots for knowledge workers: Self-learning agents connecting information and skills (2002) Intelligent Agents and Their Applications (Studies in Fuzziness and Soft Computing), 98, pp. 59-79. , L. C. Jain, Zhengxin Chen, Nikhil Ichalkaranje (eds.), Springer, New YorkDöben-Henisch, G., Klöckner, M., Agents with consciousness - Knowbotic-interface project (1995) KIP - Technical Report, , INM - Institut für Neue Medien - Daimlerstr. 32 Frankfurt, Germany - Augus

SEMIONICS: A PROPOSAL FOR THE SEMIOTIC MODELING OF ORGANIZATIONS

In this paper, we present Semionics, a contribution to the field of Computational Semiotics, and propose its use in order to build and simulate models of organizations. Computational Semiotics refers to a research area where semiotic techniques are used in order to synthesize semiotic processes in computers and computer-based applications. Semionics is the main technology developed by our research group, based on Peircean semiotics, with the aim of providing both modeling and simulation artifacts for the design of such semiotic systems. Here we present the main backgrounds of semionics- the semionic network- what it is and how it works. Further, we show an application example of a semionic network for the modeling and simulation of a small business organization

Vocabulary Agents And Conscious Action Selection For Content Management In A Language Teaching Environment

This work proposes an agent-based architecture for Intelligent Language Tutoring Systems (ILTS) with content selection and sequencing mechanism that treats each lexeme of the target language (L2) as an autonomous agent whose goal is to be learned. This strategy creates a bottom-up approach that is flexible to adapt to changes in the pedagogical goals and to reproduce the gradual and contextualized nature of the first language (L1) acquisition. The proposed architecture is based on three main pillars: (i) the lexeme-agents compete for a limited resource, the course interface; (ii) the images used in the course scenes have metadata that describe them semantically, influencing the behavior of the agents and (iii) an ontology of L2 defines the semantic and syntactic relations of its lexemes and then underpins the action selection. © 2011 IADIS.127130Ávila, I., Alternative neighborhood configurations in an ABMS model to estimate the adoption of telecenters in Brazil (2009) IADIS Computer Science and Information Systems, 5 (4), pp. 51-65Ávila, I., Redes sociais e disseminação de inovações tecnológicas: uma modelagem por agentes aplicada ao caso da TV digital brasileira (2006) Cadernos CPqD Tecnologia, 2, pp. 27-38Ávila, I., Gudwin, R., Geração e sequenciamento automáticos de lexemas e sentenças em Sistema Tutor Inteligente para ensino de línguas (2010) Proc. of SBIE 2010, , João Pessoa, BrazilBaars, B.J., Franklin, S., How conscious experience and working memory interact (2003) Trends in Cognitive Sciences., 7, pp. 166-172Heilman, M., Eskenazi, M., Language learning: Challenges for intelligent tutoring systems (2006) Proc. of the Workshop of Intelligent Tutoring Systems for Ill-Defined Domains at the 8th Intl. Conf. on Intelligent Tutoring Systems, pp. 20-28. , Jhongli, TaiwanPors, L., Conception of multiagent system integrating naturalistic decision roles: Application to maritime traffic (2009) IADIS Computer Science and Information Systems, 5 (4), pp. 66-81Mitrovic, A., Weerasinghe, A., Revisiting ill-definedness and the consequences for ITSs (2009) Proc. of the 14th Intl. Conference on Artificial Intelligence in Education AIED2009, pp. 375-382. , Brighton, United KingdomNegatu, A.S., Franklin, S., An Action Selection Mechanism for "conscious" Software Agents (2002) Cognitive Science Quarterly., 2, pp. 363-38