1. MAZETTE: Multi-agents MUSETTE for sharing and reusing ontologies Jesus Arana, Salima Hassas and Yannick Prié 28 October 2004 Claude Bernard University, Lyon 1 Lyon Research Center for Images and Intelligent information Systems WOSE 2004

2. 2 Motivation To modelise the persons that work in the creation of learning distance courses in order to create an application to assist them taking into account the users’ experience. To modelise how they work, in order to create assistances based in their traces to reuse the way they work, creating common sources of knowledge (ontology co-construction) in a emergent way. WOSE 2004

3. 3 Plan Motivation The context : documentary spaces, collective tasks, ontologies and documents. Modelling and using experience through MUSETTE. MAZETTE Use scenarios Our application and its domain Conclusion, future works WOSE 2004

4. 4 Context of study Documentary space, – Documents, annotations and personal and collective ontologies Collective task – Sharing a documentary space to realize a computer-mediated task. WOSE 2004

5. 5 Ontologies Provide the common vocabulary of a specific domain defining terms meaning and relations. [Gomez-Perez, 1999] Document Numeric documents, files and that are part of the user’s documentary space. … Context of study WOSE 2004

6. 6 MUSETTE Approach « Modeling the USEs and Tasks for Tracing Experience » MUSETTE USER-SYSTEM INTERACTION OBSERVATION & EXTRACT OF USER TRACES EXTRACTION OF SIGNIFICANT EPISODES USER ASSISTANCE WOSE 2004

7. Observer Agent Observer Agent Use Model Observation Trace Generation User Interaction Observed System Observed System Assistant Agents Episodes Reuse Observation Model Episodes Extraction Generic Trace Analyser Task Signature 1 Task Signature 1 Task Signature 2 Task Signature 2 Episodes Primitive Trace Episodes Extraction Task Signature 1 Task Signature 1 Task Signature 2 Task Signature 2 Episodes Generic Trace Analyser Assistant Agents Assistant Agents Episodes Reuse MUSETTE Approach. Observer Agent Observer Agent Observation Trace Generation Observation Model Use Model Primitive Trace WOSE 2004

8. 8 Observable Object of interestObservation Event Relations Entity Transition 5Transition 6 Transition Link1 Fr Link2 Page 1 Page 2 Fr Persistence Click1 Lang1 Bm1 En Page 2 Use model Image Link Cust Image Page Lang Sav Bm Click Constraints Use Model and a simple trace WOSE 2004

9. 9 Explained Task Signatures Examples (EXTASI’S) Task Signature : Bookmarking un interesting site Page link Click Page bm Inner Page Covering Page Same site Allows to retrieve the inner page Task Signature : Changing the language Page Trait lang This page is prefered in this language WOSE 2004

10. 10 Domain Apply model -> Create application Modelise the persons that create learning distance courses in order to conceive an application to assist users the creation of the courses. WOSE 2004

11. 11 Mazette Approach Mazette= Multi-Agents MUSETTE Mazette vs Musette Objective T o provide assistance based on the sharing and reuse of users’ experience, facilitating the co-construction of ontologies, by articulating them or unify them. WOSE 2004

12. 12 Mazette Approach ALTER EGO Use Model Trace generation WOSE 2004 Query EXTASI Storing

13. 13 … Mazette Approach Use Model Query Trace generation EXTASI Stockage User 1 Documentary space ALTER EGO Use Model Trace generation ALTER EGO Query EXTASI Storing Use Model Query Trace generation EXTASI Storing User 1 Documentary space ALTER EGO Use Model Query Trace generation EXTASI Storing User 3 Documentary space ALTER EGO Use Model Query Trace generation EXTASI Storing User 2 Documentary space ALTER EGO Ag

14. 14 Collective assistance Reactive agents will modelise and extend the personal experience in a way of a global graph. Standard and collective assistance Standard assistance The system with just one user assistance. WOSE 2004

15. 15 Mono-user Assistance The system would: Obtain the historic changes in his documentary space in a defined date, Show the different documents annotated with the same ontology, Obtain the websites that has been bookmarked the same date than a specific web site has bookmarked. File mazette.doc Edit/Modify Send mail Attach file Save document File mazette.doc as Ontolog Info Systems Clustering ontology has ontology concept Annotate annotate with WOSE 2004

16. 16 File mazette.doc User 1 Edit/Modify Send mail Attach file File mazette.doc User 2 mail attachment Accept changes Edit/Modify Save document File mazette.doc as Ontolog Info Systems Clustering ontology has ontology concept Annotate annotate with Save document as File mazette.doc Annotate with Knowledge sharing Wrappers has annotate concept Collective Assistance WOSE 2004

17. 17 File mazette.doc User 1 Edit/Modify Send mail Attach file File mazette.doc User 2 mail attachment Accept changes Edit/Modify Save document File mazette.doc as Ontolog Info Systems Clustering ontology has ontology concept Annotate annotate with Save document as File mazette.doc Annotate with Knowledge sharing Wrappers has annotate concept File mazette.doc Reactive agents WOSE 2004

18. 18 Task Signature : Document Annotation by a Ontology’s concept This document is annotated with this concept Explained Task Signatures, Assistance for Multi-users The system would: Tell if the two concepts are from the same ontology, Propose the user to add the concept to his ontology, Ask the user, if he wants to propose a concept to merge the ontologies. Create a relation between the two concepts asking the user if he agrees and to propose the type of relation. File Concept AnnotateFile_Annotated WOSE 2004

19. 19 Ontology Graph Modelisation relation [Mitra & al., 2000], A Graph-Oriented Model for Articulation of Ontology Interdependencies. Interdependencies. WOSE 2004

20. 20 Interface will provide users with the possibility of: – Building uses traces of him-self, – Managing their personal ontologies, – Annotating parts of documents using concepts of his ontologies, – Getting assistance by visualizing task-oriented episodes of his experience trace, related to several extasis. Our application WOSE 2004

21. 21 Mazette consists in the application of the Musette approach extended to several users, during the realization of a collective task. The alter-ego agent accumulates the experience from the interaction of the user in his documentary space. Mazette will allow us the sharing and reuse of the users’ experience, as well as the generation of ontologies co-constructed by the interaction of users in their workspaces. Conclusions and Future Works WOSE 2004

22. 22 Current work – development of the Mazette tool Annotating Tracing experience Single user assistance Multi-agent assistance – modeling collective traces as a graph extension of task signatures Future work – automatic tracing … Conclusions and Future Works WOSE 2004

23. 23 Thanks for your attention...

24. 24 It will be constructed in Java by its portability. It will be compliant with the FIPA specifications. His MAS system will be achieved by reactive agents under JADE. The application

25. 25 Why multi agents? Because Agents can interact in an environment in an autonomous way. Data is descentralized Agents interaction: Agents can be affected by other agents or by humans in pursing their goals and executing their tasks.