PLANSERVE Knowledge acquisition & Ontological engineering for AI Planning applications

2 08/06/2003Christophe Doniat Knowledge acquisition Team UTT - TechCICO Université Technologique de Troyes 10, rue Marie Curie – BP 2060 – Troyes, France

3 08/06/2003Christophe Doniat Knowledge TechCICO Different aspects of research & development Techniques of knowledge capture and acquisition Data/text- mining Machine learning: induction by examples Ontological engineering: which representation and methods? Interactive acquisition process How to manage the user (expert or non expert) in the loop? Applications for AI Planning field KATOOL: contribution to PLANFORM project Ontology libraries (e. g. knowledge-based marketplace) Collaborations University of Marseille Universities of Salford, Huddersfield and Durham

4 08/06/2003Christophe Doniat Present project HyperTopic: contribution to a knowledge- based marketplace management system Methodology and tool for the systematic building of ontologies with multi-point of views User-centred model for performance measure

5 08/06/2003Christophe Doniat Potential contribution Evolving of methodology for the definition of ontologies for AI Planning & scheduling: A concept of knowledge-based marketplace A typical case is the logistics domain with the robot positioning subset Extension of existing KATOOL software: is to deal with re-use and enrichment of ontologies (interoperatibility) Framework architecture

6 08/06/2003Christophe Doniat Definition of ontologies issues for AI Planning A first problem is to define strong fragments of ontologies. We do not want to start the acquisition process from scratch! A second problem is to guide the user (expert or non expert) during the process of knowledge acquisition by measure his/her performance A third problem is a shared view between ontologies librairies and strong planning and scheduling algorithms

7 08/06/2003Christophe Doniat Extension of existing KATOOL software KATOOL can capture knowledge from user through a question-driven process, actually Re-use of existing ontologies needs more integration => which framework? Interoperability between a new ontology and the ontology librairie

8 08/06/2003Christophe Doniat Framework architecture The problem is still the same: how do we can represent knowledge and its related processes to deal with the evolution of it? Common knowledge representation: ontologies issues Common knowledge definition & (re)-use: ontological engineering issues

9 08/06/2003Christophe Doniat Conclusions The underlying role of knowledge acquisition and the HCI techniques Guidelines for user User-centred model to measure performance The management of ontologies libraries for AI planning and scheduling community A knowledge-based marketplace concept Advanced features: Support of Ontological engineering techniques & Semantic Web languages Dynamic and adaptative mapping between ontologies and planning/scheduling algorithms