1. Copyright Cesar Augusto Tacla@UMR 6599 HEUDIASYC, UTC, 2003 1 A M ulti-Agent A rchitecture for K nowledge A cquisition Cesar TACLA* Jean-Paul BARTHES {cesar.tacla, barthes}@utc.fr CNRS UMR 6599 HEUDYASIC Université de Technologie de Compiègne Compiègne, France *CEFET / CAPES Curitiba, Brazil

2. Copyright Cesar Augusto Tacla@UMR 6599 HEUDIASYC, UTC, 2003 2 Introduction Problem Lost of K = Time + Spread information + Dynamic groups How to organize knowledge in Research and Development teams (R & D) >> reuse of gained experience Why R & D groups ? –serious constraints on time –top-down methods are difficulty to apply –activities are rich, complex and sometimes unexpected

3. Copyright Cesar Augusto Tacla@UMR 6599 HEUDIASYC, UTC, 2003 3 KM Environment Approach –An environment that integrates humans and artificial agents –Cooperative construction of a distributed group memory –Guidelines Minimize effort from knowledge engineering Minimize effort from knowledge producers

4. Copyright Cesar Augusto Tacla@UMR 6599 HEUDIASYC, UTC, 2003 4 KM Environment Requirements for the KM Environment 1.Nature of K: technical K + design K 2.KM env functions: document management, and aid to the externalization and internalization 3.Integration: transparent, integrated into the individuals day- to-day activities, bottom-up K acquisition, distributed (there is no central node or filter) 4.Different perspectives: each individual organizes K according to her preferences, distributed

5. Copyright Cesar Augusto Tacla@UMR 6599 HEUDIASYC, UTC, 2003 5 KM Environment A KM Environment is –a distributed group memory –composed by individual memories, –where individuals work cooperatively

6. Copyright Cesar Augusto Tacla@UMR 6599 HEUDIASYC, UTC, 2003 6 KM Environment Docs Capture Clusters of Docs Classified docs + clusters Personal memory ClassifyCluster Conceptual Models Construction of a personal memory

7. Copyright Cesar Augusto Tacla@UMR 6599 HEUDIASYC, UTC, 2003 7 KM Environment Personal memory 1 Preserve Conceptual Models Sources Project memory Personal memory i Familiarize Validate Personal memory 2 Personal memory 3 Research Cooperative processes

8. Copyright Cesar Augusto Tacla@UMR 6599 HEUDIASYC, UTC, 2003 8 KM Environment K item evolution graph: distributed graph KI 1 KI 2 KI 3 Derived from modifies KI 4 refers to KI 5 replaces A’s memoryB’s memoryC’s memory KI = Knowledge Item

9. Copyright Cesar Augusto Tacla@UMR 6599 HEUDIASYC, UTC, 2003 9 MA architecture Built on the OMAS platform –Open Multi-Agent System Features –Cognitive agents –Two agent types: Service and Personal Assistant –Coterie Agents share the same local network Communication is in broadcast Contract-net / Simple protocol (request, answer, inform) SPA

10. Copyright Cesar Augusto Tacla@UMR 6599 HEUDIASYC, UTC, 2003 10 MA architecture User scope components –Each user has a staff of agents –Staff agents run on the same computer –Service agents in the staff are dedicated to the assistant agent Organizer User A’s staff S PA Assistant  Interface  Capture operations+docs  Save (operations, docs)  Cluster  Classify

11. Copyright Cesar Augusto Tacla@UMR 6599 HEUDIASYC, UTC, 2003 11 MA architecture Repository Agent Transfer Agent GW or DB X S S Project Agent Project scope K preservation (preserve) Sources of the conceptual models (familiarize) Communication Doc retrieving/storing Access rights Components project level Agents run on different machines

12. Copyright Cesar Augusto Tacla@UMR 6599 HEUDIASYC, UTC, 2003 12 MA architecture Repository Agent Transfer Agent GW or DB X A’s staff S PA S S Project Coterie (LAN) Project Agent B’s staff S PA Project scope organizer Proposed Architecture

13. Copyright Cesar Augusto Tacla@UMR 6599 HEUDIASYC, UTC, 2003 13 MA architecture Desktop operations Fred’s staff S PA Organizer  Save operations + docs  Cluster  Classify Assistant  Capture operations + docs P S S S PA S S Fred Coterie members  Reuse  Retrieve  Diffuse  Validate

14. Copyright Cesar Augusto Tacla@UMR 6599 HEUDIASYC, UTC, 2003 14 MA architecture Personal Memory A Personal Memory B Project Memory Derived from modify replace Distributed group memory Source of a conceptual model

15. Copyright Cesar Augusto Tacla@UMR 6599 HEUDIASYC, UTC, 2003 15 Conclusion Future work –Define the semantics for the relations in the evolution graph –Define a protocol for coordinating the validation process Important issues –Specification of the minimal components (functions and knowledge items) for a KM environment. –The notion of staff of agents dedicated to a user –Aid the user to formalize his/her Knowledge -> gradual formalization of information –Augmenting the knowledge sharing (expected !) –Decreasing the information load