A M ulti-Agent A rchitecture for K nowledge A cquisition

1. AMulti-Agent Architecture for Knowledge Acquisition Cesar TACLA*Jean-Paul BARTHES {cesar.tacla, barthes}@utc.fr CNRS UMR 6599 HEUDYASICUniversité de Technologie de CompiègneCompiègne, France *CEFET / CAPESCuritiba, Brazil

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. 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 KM Environment

4. KM Environment • Requirements for the KM Environment • Nature of K: technical K + design K • KM env functions: document management, andaid to the externalization and internalization • Integration: transparent, integrated into the individuals day-to-day activities, bottom-up K acquisition, distributed (there is no central node or filter) • Different perspectives: each individual organizes K according to her preferences, distributed

5. A KM Environment is a distributed group memory composed by individual memories, where individuals work cooperatively KM Environment

6. Cluster Classify Classifieddocs+clusters Clustersof Docs ConceptualModels KM Environment Construction of a personal memory Capture Docs Personal memory

7. Research Validate Personal memory 2 Personal memory 3 KM Environment Cooperative processes Projectmemory ConceptualModels Sources Preserve Familiarize Personal memory 1 Personal memory i

8. K item evolution graph: distributed graph KM Environment A’s memory B’s memory C’s memory refers to Derived from KI1 KI2 KI4 modifies replaces KI3 KI5 KI = Knowledge Item

9. 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) MA architecture S PA

10. Interface • Capture operations+docs • Save (operations, docs) • Cluster • Classify 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 User A’sstaff Assistant PA Organizer S

11. Communication K preservation (preserve)Sources of the conceptual models (familiarize) Doc retrieving/storingAccess rights MA architecture Components project level TransferAgent Repository Agent Project Agent X S S GW or DB Project scope Agents run on different machines

12. MA architecture TransferAgent ProposedArchitecture Repository Agent Project Agent X S S GW or DB A’s staff PA ProjectCoterie(LAN) Project scope S organizer B’s staff PA S organizer

13. PA PA PA S S S S P S MA architecture Fred Desktop operations Assistant • Capture operations + docs Organizer • Save operations + docs • Cluster • Classify PA S Fred’sstaff Coterie members • Reuse • Retrieve • Diffuse • Validate

14. MA architecture Project Memory Distributed group memory Source of a conceptual model Personal Memory B modify Personal Memory A Derived from replace

15. Conclusion • 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 • Future work • Define the semantics for the relations in the evolution graph • Define a protocol for coordinating the validation process