Self-organizing decision-making system

P. M. Ivanov ; Z. V. Nagoev

News of the Kabardin-Balkar scientific center of RAS, no. 5 (2012), pp. 30-37.

Résumé

The processes of the self-organizing generating semantically loaded attractors, interpreted in terms of formation of processes of a reasoning are considered. The intellectual behavior of a macrosystem at top levels is reached at the expense of recursiveness of the cognitive architecture allowing to incapsulate cognitive functions in multiagent cognitive blocks of various level of complexity. As a formal basis of similar macrosystems the recursive determined abstract automatic machine is applied. Use of self-organizing systems of the decision-making based on distributed multiagent collectives, as a base platform for formation of decentralized integrated anthropocentric managements of enveloping intelligence is proved.

Détail

Keywords: cognitive architecture, multiagent system, recursive agent, artificial intelligence, intelligent decision-making
Mots-clés : ambient intelligence.

Bibliographie

[1] V. M. Glushkov, Vvedenie v kibernetiku, Pechataetsya po postanovleniyu nauchnogo soveta po kibernetike AN USSR, Izd-vo AN USSR, Kiev, 1964

[2] V. I. Gorodetskii, O. V. Karsaev, V. V. Samoilov, S. V. Serebryakov, “Prikladnye mnogoagentnye sistemy gruppovogo upravleniya”, Iskusstvennyi intellekt i prinyatie reshenii, 2009, no. 2

[3] P. M. Ivanov, “Avtomatno-algebraicheskie modeli v informatsionnykh tekhnologiyakh”, Materialy II mezhdunarodnoi konferentsii i intellektualnye sistemy i sredy> \date 23-29 dekabrya 2011 g., v. I, Izd-vo KBNTs RAN, Krasnaya Polyana, 4–15 pp.

[4] P. M. Ivanov, Algebraicheskoe modelirovanie slozhnykh sistem, Izd-vo , M., 1996, 272 pp.

[5] V. Ch. Kudaev, Z. V. Nagoev, O. V. Nagoeva, “Rekursivnye agenty dlya zadach modelirovaniya intellektualnogo prinyatiya reshenii na osnove samoorganizatsii multiagentnykh kognitivnykh arkhitektur”, Izvestiya KBNTs RAN, 2012, no. 4 (48)

[6] A. A. Letichevskii, Yu.V. Kapitonova, “Insertsionnoe modelirovanie”, Pratsi mizhnar. konf. «50 rokiv Іnstitutu kibernetiki im. V.M. Glushkova NAN Ukraïni», Vid-vo IK NANU, Kiïv, 2008, 293–301 pp.

[7] Z. V. Nagoev, “Formalizatsiya agenta dlya zadachi sinteza intellektualnogo povedeniya na osnove rekursivnoi kognitivnoi arkhitektury”, Materialy Mezhdunarodnogo kongressa po intellektualnym sistemam i informatsionnym tekhnologiyam IS IT 12, v. II, 2012 (2–9 sentyabrya, Divnomorskoe)

[8] Z. V. Nagoev, “Intellektualnaya sistema na osnove fraktalnoi multiagentnoi neironnoi plastichnoi kognitivnoi arkhitektury”, Materialy Mezhdunarodnogo kongressa po intellektualnym sistemam i informatsionnym tekhnologiyam IS IT 11, v. III, 2011, 5–10 pp. (2–9 sentyabrya, Divnomorskoe)

[9] Styuart Rassel, Piter Norvig, Iskusstvennyi intellekt: sovremennyi podkhod (AIMA) Ārtificial Intelligence: A Modern Approach (AIMA), 2-e izd., Vilyams, M., 2007, 1424 pp.

[10] V. B. Tarasov, Ot mnogoagentnykh sistem k intellektualnym organizatsiyam, Editorial URSS, M., 2002, 352 pp.

[11] M. L. Tsetlin, Issledovaniya po teorii avtomatov i modelirovaniyu biologicheskikh sistem, Nauka, M., 1969

[12] M. L. Tsetlin, “O povedenii konechnykh avtomatov v sluchainykh sredakh”, Avtomatika i telemekhanika, 22:10 (1961), 1345–1354

[13] A. Letichevsky, D. Gilbert, “A Model for Interaction of Agents and Environments”, Resent Trends in Algebraic Development Techniques, 1827 (1999), 311–328 | DOI

[14] Lev Naumov , Anatoly Shalyto, “Automata Theory for Multi-Agent Systems Implementation”, Proceedings of International Conference Integration of Knowledge Intensive Multi-Agent Systems: Modeling, Exploration and Engineering, IEEE Boston Section, Boston, 2003, 65–70 pp.