Virtual Knowledge Communities for Corporate Knowledge Issues

1. Virtual Knowledge Communities for Corporate Knowledge Issues Pierre Maret INSA de Lyon, LIRIS, France Mark Hammond Imperial College London, England Jacques Calmet University of Karlsruhe, IAKS, Gernamy

2. Overview • Dynamical distributed knowledge management • Enterprise considered as a distributed computational paradigm • Agent-oriented approach • Modeling dynamical knowledge exchanges within agents • Concept of “Virtual knowledge communities”

3. Agenda • Knowledge Management • MAS for corporate knowledge • Liberal approach of agents and Agent Oriented Abstraction • Agent’s Knowledge • Virtual knowledge communities • Modeling • Processes • Social behavior • Implementation and example • Results, Perspectives

4. Enterprise Knowledge Management • What is it? Models, techniques, methods related to the improvement of activity through formalizing, exchanging, reusing knowledge • Key words • Knowledge intensive tasks • Ontology • Information, Data, Documents • Community of practice, community of interest

5. Enterprise Knowledge Management • Most approaches to knowledge management rely on centralization and objectivity (Database paradigm) : One database schema and one ontology for structuring and indexing the organization’s universe. Eventually distributed databases. • Incompatible with the very nature of knowledge: subjective, distributed and contextual • Bonifacio: "all perspectival aspects of knowledge should be eliminated in favor of an objective and general representation of knowledge". • Authors emphasizes distributed knowledge management and knowledge nodes. O2 O3 Ontology 1 translation translation Knowledge Node 1 KN 2 KN 3

6. Corporate Knowledge - Definition • Overall knowledge possessed within an organization + Abilities for exchanges • Comments: • Covers individuals, data bases, documents, sensors… • Large definition of knowledge: everything that can be useful for acting within the organization (piece of information, predicate, protocol…) • Linked to the agents’ decision mechanism : domains of interests, knowledge exchange processes

7. MAS for Knowledge Management • Overview of agents in KM: [Dignum 04] • Motivations for using MAS approach Compatible with • Distribution of data, capabilities, responsibilities. • Autonomy AND complex interactions (negotiation, information sharing, coordination) • Dynamic behavior and responsive to changes

8. MAS for Knowledge Management • Two perspectives : Agents to implement KM functionalities Agents to model the organizational KM environment Needs: Broad and generic view on knowledge within the organization (Content, Processes, …)

9. Bases of our proposal • Liberal approach of agent societies • Agent-Oriented Abstraction (AOA)

10. Liberal approach of agents societies [Calmet 03] (Esaw) • Model for a society of agents based on sociology principles (Weber) Main contents • No general goals imposed to agents (goals arise from agents’ actions) • The system is open and security is assumed • Knowledge heterogeneity must be supported

11. Agent-Oriented Abstraction (AOA) [Calmet 04] (to appear) • An agent is composed of - Annotated Knowledge - A Decision Mechanism • A generic approach for agents and society of agents • The present work concentrates on the knowledge component

12. Corporate Knowledge, 2nd definition • Overall knowledge possessed by agents of an organization • Comments: • Agents: includes individuals and automata • Large definition of knowledge (includes cooperation ability) • Linked to the agents’ decision mechanism : actions related to knowledge processes (exchanges, domains of interests) Our goal : Model the organizational environment for CK and agent’s ability to share knowledge

13. Agent’s Knowledge • Knowledge Cluster : structured knowledge related to a given area (task, topic…), expressed in terms of predicate, concepts, actions (+ sub-cluster: recursive definition) • Knowledge instances = instances of terms • Agents’ knowledge = a knowledge cluster + knowledge instances

14. Agent’s Knowledge Comments • Knowledge varies from agent to agent : agents do not have the same view of the world • Knowledge evolves with time: inherent knowledge + knowledge production and acquisition • Instances • Knowledge cluster • Fully compliant with very nature of corporate knowledge

15. Sharing Knowledge • Agent possess knowledge • They are in charge of given tasks and • They can increase their efficiency thanks to knowledge exchanges =>Modeling agent’s behavior in knowledge sharing =>Added feature which must be opened, dynamic, agent-driven : Virtual Knowledge Communities

16. Virtual Knowledge Communities VKC • A VKC: first class abstraction • A topic, a leader, members, a space • Topic: subpart of leader’s knowledge • Leader: any agent • Members: any others agents • Space: message buffer controlled by the leader

17. VKC Processes • Initiate: an agent proposes a topic (sub-cluster and/or instances) • Join: an agent is interested by a community topic (cluster intersection) • Inform: an agent proposes an extension to a topic • Request: an agent asks for extensions of a topic • Leave, delete… • Agents can create and join many communities

18. Agent’s behavior • Agents have an added layer • Additional goals: in terms of knowledge cluster to extend • Examples of behavior: • Individualistic agent: acts to reach its goals (ex: kill/leave a community once completing knowledge it required) • Social agent: acts to help others agents (ex: join all communities related to its knowledge)

19. Implementation & Example • Jade Plate-form + Java agents Agent1: Jose Agent2: Mark J-Item J-Book is_a J-Item MyBook instance_of J-Book J-Item = Item M-Item M-Item = Item

20. Implementation & Example • Jade Plate-form + Java agents Agent1: Jose Task T1 Agent2: Mark Task T2 J-Item J-Book is_a J-Item MyBook instance_of J-Book J-Item = Item M-Item M-Item = Item Additional behavior Goal: M-Item Create community on “Item”

21. Implementation & Example • Jade Plate-form + Java agents Agent1: Jose Agent2: Mark J-Item J-Book is_a J-Item MyBook instance_of J-Book J-Item = Item M-Item M-Item = Item Goal: M-Item Join Mark’s community on “Item”

22. Implementation & Example • Jade Plate-form + Java agents Agent1: Jose Agent2: Mark J-Item J-Book is_a J-Item MyBook instance_of J-Book J-Item = Item M-Item M-Item = Item Goal: M-Item Informs about J-Book is_a Item MyBook instance of J-Book

23. Implementation & Example • Jade Plate-form + Java agents Agent1: Jose Agent2: Mark J-Item J-Book is_a J-Item MyBook instance_of J-Book J-Item = Item M-Item M-Item = Item Introduces M-Book = J-Book

24. Implementation & Example • Jade Plate-form + Java agents Agent1: Jose Agent2: Mark J-Item J-Book is_a J-Item MyBook instance_of J-Book J-Item = Item M-Item M-Book is-a M-Item M-Item = Item M-Book = J-Book MyBook instance of M-Book

25. Results • Knowledge exchanged depending on agent’s goals and decisions • An organizational environment for corporate knowledge • Implementation of the liberal approach of agents in the context of corporate knowledge: openness, autonomy, dynamicity in knowledge exchange • Agent-Oriented Abstraction: emphasizes duality / complementarities in-between Knowledge and Decision

26. Perspectives • Application to knowledge filtering within organization, personal assistant software • Security issues: ensure only trustworthy agents • Modeling agent’s knowledge: annotations as proposed in AOA (traditional agent plate-forms are not sufficient) • Introducing more complex behaviors/roles