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Heriot -Watt University MACS, Edinburgh lilia@macs.hw.ac.uk

Towards a Logical Framework For Knowledge Management in D igital E conomy Lilia Georgieva and Imran Zia KES-AMSTA 2009 June, 5 th. Heriot -Watt University MACS, Edinburgh lilia@macs.hw.ac.uk. Structure. Background and motivation

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Heriot -Watt University MACS, Edinburgh lilia@macs.hw.ac.uk

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  1. Towards a Logical Framework For Knowledge Management in Digital Economy Lilia Georgieva and Imran Zia KES-AMSTA 2009 June, 5th Heriot -Watt University MACS, Edinburgh lilia@macs.hw.ac.uk

  2. Structure • Background and motivation • Knowledge management in digital economy • Formalisation and verification • Case studies

  3. Challenges in digital economy • Knowledge generation • Knowledge creation and sharing • Analysis of knowledge management models • Adaptation of knowledge management models • Formalisation of knowledge management • Verification and security

  4. Background & Motivation • Languages for knowledge modelling -modal logic; -description logic; -epistemic logic; -process logic. • Model checking and verification. • Benefits. • Case studies.

  5. Knowledge Management Knowledge management is: • a mix of contextual information, experience and rules • an integrated approach to identifying, capturing, evaluating, retrieving and sharing all of enterprises information assets. Types of knowledge in digital economy: descriptive, static, updated, dynamic, interactive.

  6. Example of Static KM Model (Kimas 2003) Information processing view of knowledge work = limited to static combination of natural language.

  7. Our modelling language • Prepositional logic formulas + two (basic) modal logic operators : ◊ (diamond) possibly □ (box) necessary • For proposition letters set { p, q, r…}, if , are modal formulas, then so are: T,  , ¬ , v, , → , ↔ , ◊ , □ .

  8. Epistemic Logic • Logic for knowledge and belief. • Provides an insight in to properties of individuals and groups. • Knowledge is implicitly represented in the agent’s information state.

  9. Standard Knowledge Axioms • (K1) Ki ¬¬p→ Ki p, • (K2) ¬Ki¬p→Ki p, • (K3)¬Ki p→Ki¬ p, • (K4) Ki p→ Ki Ki p • (K5) Ki p ۸ Ki (p→q) → Ki q, • (K6) Ki (p۸q) → Ki p۸ Ki q, • (K7) Ki (p٧q) → Ki p٧ Kiq, • (K8) Ki ¬ (p۸q) → Ki ¬ p٧ Ki ¬ q, • (K9) Ki ¬ (p٧q) → Ki ¬ p۸ Ki ¬ q, • (K10) Ki Kj p → Ki p.

  10. Knowledge Management Streams • Knowledge sharing • Determine knowledge • Determine knowledge available • Determine knowledge gap • Knowledge lock • Knowledge utilisation • Knowledge evaluation

  11. Knowledge management framework The framework is based on the following steps: • Knowledge stream specification. • Knowledge stream formalisation in epistemic logic. • Translation into MAP encoding. • Semantic interpretation (FIPA semantics). • Stream verification. • Analysis of stream behaviour.

  12. Reject REJECTS (M) REJECTS (M) SHARES (M) Shares (M. agent iknowsfact agent jsharesfact Initial SHARES (M) ACCEPT (M) ACCEPT (M) Accept Graphical Representation of Knowledge Sharing Protocol

  13. Model checking • Input: A finite state model of the knowledge process. A specification (requirement) regarding the model. • Algorithm: Check if the system design satisfies the specification. If not, generate a system run which violates the specification (counter example).

  14. Model checking knowledge processes • SPIN is a verification tool used for data communication protocols, multi-threaded code, client-server applications. • SPIN verification is focused on proving correctness of processes interactions; not much importance is given to internal computations. • Processes refer to components that interact with each other. • Interaction is synchronous or asynchronous message passing.

  15. Knowledge sharing Initial state – (Kjq) (Kip) Generated axioms Ki p → Ki Ki p (K4) Kj q → Kj Kj q (K4) ¬Kip →Ki¬ p , (K3) ¬Kjq →Kj¬ q , (K3) ¬Ki¬ p →Kip, (K2) ¬Kj¬ q →Kjq , (K2) Ki ¬ ¬ Kjq → Kiq , (K1) End State Ki (p۸q) → Ki q۸ Ki p, (K6)  Example properties: Data is always sent from the agent with the latest data to the other agent. Exactly one agent is the active knowledge sharer at any point of time. • End process –insert end process

  16. Related work on KM Knowledge management models • Static KM models • Computational models • Diagramatic KM models Related work on Model Checking • Agent communication • Fairness, liveness, termination. • Security of information.

  17. Thank you!

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