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INFORMATION AND KNOWLEDGE MANAGEMENT (SBEM)

INFORMATION AND KNOWLEDGE MANAGEMENT (SBEM) Lecture: block lecture with oral exam at the end of the block Language of instruction: English Course rationale

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INFORMATION AND KNOWLEDGE MANAGEMENT (SBEM)

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  1. INFORMATION AND KNOWLEDGE MANAGEMENT (SBEM) Lecture: block lecture with oral exam at the end of the block Language of instruction: English Course rationale Economics and management include core studies in complex systems involving all areas of system sciences mainly complexities involving information flow and information structuring into knowledge and its representation. Tools needed in such studies include mathematics with soft modelling, decision support, simulation and knowledge representation. The course outlined in this document is designed as an essential part of this educational process. Course description: The lecture will cover general field of information and knowledge management. Typical lecture topics include the following: Modern information systems Decision support systems Information modelling Information structuring into knowledge Knowledge representation Knowledge management Soft modelling and Artificial Intelligence techniques Decisional DNA E-Community Content and mode of delivery: LECTURE AND DISCUSSIONS Grading policy: Oral exam – 100% Text: Reading and research related to the lecture is based on material available in the library or on the Internet. The lecture will be based in some parts on the books: • E Szczerbicki “Information Management: Modelling, Analysis, and Simulation Perspective”, GTN Gdansk, 2004. • Szczerbicki, E; Nguyen, N “Smart Information and Knowledge Management: Advances, Challenges, and Critical Issues”, Springer Berlin, 2010. • N Thanh, Szczerbicki, E “Intelligent Systems for Knowledge Management”, Springer Berlin, 2009. • Contact with course coordinator: • Prof E Szczerbicki: Edward.Szczerbicki@zie.pg.gda.plGmach B, 820 ph 21-95 • Information and knowledge management links are easy to find using any of the popular search engines. Typical links are also listed on the page http://www.zie.pg.gda.pl/zwi/. You can also find lecture notes there.

  2. INFORMATION AND KNOWLEDGE MANAGEMENT IN COMPLEX SYSTEMS

  3. Lecture notes: http://www.zie.pg.gda.pl/zwi/ • Nine parts of presentations (over 400 slides) • Two recent conference papers on case studies

  4. Ksiazka jest do nabycia w GTN, Gdansk. Zamowienia mozna przesylac do Biura Towarzystwa e-mailem gtn@3net.pl , faksem 305-81-31. Ksiazka jest wysylana poczta z faktura VAT. Sprzedaz prowadzi tez Ksiegarnia Naukowa przy ul. Lagiewniki 56 w Gdansku

  5. Intelligent Systems for Knowledge Management Series: Studies in Computational Intelligence , Springer Berlin. Nguyen, Ngoc Thanh; Szczerbicki, Edward 2009, XII, 332 p. 147 illus., Hardcover ISBN: 978-3-642-04169-3 Springer Customer Service Center GmbH Haberstrasse 7 69126 Heidelberg Germany • Call: + 49 (0) 6221-345-4301 • Fax: +49 (0) 6221-345-4229 • Web: springer.com • Email: orders-hd-individuals@springer.com

  6. Smart Information and Knowledge Management: Advances, Challenges, and Critical IssuesSeries: Studies in Computational Intelligence , Vol. 260 Szczerbicki, Edward; Nguyen, Ngoc Thanh (Eds.) 2010, X, 340 p., HardcoverISBN: 978-3-642-04583-7

  7. SOCIAL CHARACTERISTICS OF THE AGRICULTURAL, INDUSTRIAL AND INFORMATION SOCIETIES (Castells 2001, 2003)

  8. MANAGEMENT OF INFORMATION… Presentation outline: • significance and aims • methods and techniques • results so far • implementations

  9. SIGNIFICANCE AND AIMS • If all the N elements of a system are required to communicate, the amount of information transfer is likely to become unmanageable. • The above has been the reason why systems that are divided into smaller subsystems (called atomized or multi-agent or multi-component systems) are recently gaining considerable attention. • In atomized approach efficiency of components depends on quality and quantity of information flow (Jain 2001) • Our research is primarily concerned with capture of knowledge useful in structuring and evaluation of such an information flow.

  10. AUTONOMOUS AGENTS/SYSTEMS • AUTONOMOUS AGENTS CONSIST OF GROUPS OF PEOPLE, MACHINES, ROBOTS, AND/OR GUIDED VEHICLES TIED BY THE FLOW OF INFORMATION BETWEEN AN AGENT AND ITS EXTERNAL ENVIRONMENT AS WELL AS WITHIN AN AGENT • AUTONOMOUS AGENTS CAN STILL BE INTERRELATED AND EMBEDDED IN LARGER SYSTEMS, AS AUTONOMY AND INDEPENDENCE ARE NOT EQUIVALENT CONCEPTS. (E. Szczerbicki, IEEE Transactions on Systems, Man, and Cybernetics, Vol. 23, p. 1302)

  11. SOLVING COMPLEX PROBLEMS DECOMPOSITION INTEGRATION INTEGRATED SOLUTION COMPLEX SYSTEM REPRESENTATION

  12. DECOMPOSITION…..

  13. DECOMPOSITION….

  14. AND/OR CLAUSES

  15. EXAMPLE:AND/OR NOTATION

  16. SOLVING COMPLEX PROBLEMS COMPLEX SYSTEM DECOMPOSITION REPRESENTATION INTEGRATION INTEGRATED SOLUTION

  17. QUESTIONS……. • How to structure an exchange of information between a system and its uncertain, dynamic and imprecise environment? • What is better, complete information but heavily delayed, or incomplete information less delayed?

  18. INFORMATIONAL BALANCE

  19. EVALUATION OF INFORMATION FLOW

  20. ENERGY, INFORMATION AND ACTION

  21. INFORMATION STRUCTURE 1 0 0 0 0 1 0 0 0 0 1 1 0 0 1 1 X1 X2 X3 X4

  22. THE VALUE OF INFORMATION STRUCTURE C

  23. SOFT VS HARD MODELLING THEORY RICHNESS SOFT MODELLING NEURAL NETWORKS EXPERT SYSTEMS PHYSICAL MODELLING DATA RICHNESS

  24. NEURAL NETWORKS

  25. THE USE OF THE TRAINED NETWORK

  26. DECISION TREE CLASSIFIERS

  27. DECISION TREE: TESTING ON INTERNAL ENVIRONMENT

  28. SIGNED DIRECTED GRAPHS (SDG)

  29. SDG MODEL OF AN INFORMATIONAL BALANCE – FINAL SIMPLIFICATION

  30. SAMPLE OF PRODUCTION RULES RULE 12 IF an external environment of an autonomous agent is static, AND there is an interaction in the internal environment, AND the relationship between variables describing the external environment is of statistical character, THEN information structure should include observation (sensoring) and communication. RULE 13 IF an external environment of an autonomous agent is static, AND the relationship between variables describing the external environment is given by function dependence, THEN communication between agent elements does not affect the value of information structure; information flow should be restricted to observation (sensoring).

  31. SOLVING COMPLEX PROBLEMS COMPLEX SYSTEM DECOMPOSITION REPRESENTATION INTEGRATION INTEGRATED SOLUTION

  32. FIVE LEVEL HIERARCHICAL TREE OF THE OVERALL INTEGRATED SYSTEM

  33. INTEGRATION…… Reference

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