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International Conference on Complex Systems (ICCS2006)

Self-Organizing Architecture of Complex Systems

Irina Ezhkova
International Institute of Applied Technologies

     Full text: Not available
     Last modified: April 30, 2006

Abstract
Self-Organizing Architecture of complex continuously learning communicating systems is based on the principles of Cognitive Rationality, Cognitive Relativity and Cognitive Clarity (CRRC) [1]. It allows parallel and simultaneous mappings of experience, images and knowledge to orders, relations and self-organizing representations [2, 3]. Two interviewing mechanisms, the Mapping to Universal scales [4] and the Systems of Communicating Contextual Systems (C2S) [5] are described to allow automated design of the Self-Organizing Architecture. .

The Universal Scales allow cognitive and contextually normalized measurements; tuning to Cognitive and Contextual Spaces; mapping of experience to representations; symbolization, interpretation, translation and restoration of knowledge and experience. Algebra and Logic of Contexts formalize inter-contextual relations and structural similarities, such as metaphors, analogies, and associations [6].

Assessment of the Complexity of Cognitive Interface (CCI), time, risk and energy of required self-organizing efforts may be evaluated via transformation of Contextual Manifolds (concurrently, with a time delay, in parallel or simultaneously) while Shifting, Zooming in or out of interesting Contextual Perspectives [2, 7].

The principles CRRC allow automated triggering of contextual transformations. They also allow comparative modeling of consciousness versus unconsciousness and involvement of emotions, when transformations are not performed in accordance with CRRC. Based on CRRC, Self-Organizing Architecture allows sensitive anchoring to appropriate functional ontologies and prediction of efficient embodiment [2, 3, 8].

The recursive mechanism of constraint acquisition and satisfaction allow self-organizing calculi of Systems of Emergent Communicating Contextual Systems. It is based on the mechanism of Learning from Failures (L2F) to acquire a flow of self-organizing opportunities [3].

It is shown how such architecture may be inhabited by intelligent entities (such as actors, cultures, roles, “invisible hands”), which may appear as centers of semantic attraction and may be used to conduct further self-organizing activities [2, 3]. This may explain how cognition, consciousness, intelligence and cultures may arise, and how evolution may be seen and predicted as reaching its local maximums and minimums.

Areas of practical applications include simulation, modeling, analysis and prediction of real complex self-organizing phenomenon such as in genetic, biological, cultural, social and economic systems
[1, 9] as well as design, control, strategic planning and management of artificial complex systems [1,10].






References

1. Irina Ezhkova. The Principles of Cognitive Rationality, Relativity, and Clarity. Cybernetics and Systems, vol.35, 2-3:229-258, 2004.

2. Irina Ezhkova. Self-Organizing Representations, Cybernetics and Systems, vol.36, 8:860-876, 2005.

3. Irina Ezhkova. Architecture of Opportunities, Proceedings of the CRRC-06 Symposium, European Meeting on Cybernetics and Systems research, 2006, Vienna.

4. Irina Ezhkova. Universal Scales: Theory of Distinguishability, Proc. of conference on 40th
of Fuzzy Pioneers on Forging New Frontiers (BISCSE’2005), November 2005, Berkeley.

5. Irina Ezhkova. Systems of Communicating Contextual Systems, Plenary Lecture, Proc. of International Conference on Informatics’05, June 2005, Bratislava.

6. Irina Ezhkova. Knowledge formation through context formalization. Computers and Artificial Intelligence 8(4):305-322, 1989.

7. Irina Ezhkova. Relativity of Mind: Nesting Perspectives, Proc. of the Intern. Conference on Anticipatory Systems, August 2005, Liege.

8. Irina Ezhkova. Cognitive Architecture of Functional Ontology, Proceedings of the International Conference on Cognitive Science, 2006, St. Petersburg (to appear).

9. Irina Ezhkova. Natural Logic and Cognitive Economics, Proc. of International Conference on Cognitive Economics, July 2005, Sofia.

10. Luchio Bianco and Irina Ezhkova. Application of Contextual Technology for Supporting Decision Making in Transportation. Proceedings of the 7-th International Symposium on Transportation Systems: Theory and Application of Advanced Technology (IFAC TS), Tianjin, China.




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