A distributed semantic network model for a collaborative intelligent system

A methodology based on topology theory to model a semantic network for a collaborative system is given. This framework is used to support the creation of a semantic network and to define the associated intelligent cooperative system. Our methodology is illustrated via a set of agents whose knowledge-base is a semantic network. By a series of functions applied on a base of entities, issued from the application domain, a family of sets are synthesized with their subspaces correlated. The resultant subspaces and their relations form a network of elementary and complex concepts that can be naturally represented with the IDEF1x language. A prototype Multi-Agent System (MAS), set up with the Zeus platform,1 was developed for the Process Plan domain, which was used as a case study. Full correspondence among the subspaces, the semantic network IDEF1x information model and the MAS implementation is obtained by employing this framework.

[1]  Andrew Kusiak,et al.  Data modelling with IDEF1x , 1997 .

[2]  Ludwik Czaja,et al.  Minimal-Maximal Time Cause-Effect Structures , 1998, Fundam. Informaticae.

[3]  Franck Plestan,et al.  An algorithm for the structural analysis of state space: synthesis of nonlinear observers , 2001 .

[4]  Omar López-Ortega,et al.  A Java application based on an EXPRESS model for sharing flexible manufacturing resources data , 2001, ETFA 2001. 8th International Conference on Emerging Technologies and Factory Automation. Proceedings (Cat. No.01TH8597).

[5]  Anup Kumar,et al.  Intelligent feature extraction for concurrent design and manufacturing , 1995 .

[6]  Weiming Shen,et al.  Agent-based Decision-Making for Distributed Process Planning , 2001 .

[7]  Nicolas Lhuillier,et al.  FOUNDATION FOR INTELLIGENT PHYSICAL AGENTS , 2003 .

[8]  Shiu Kit Tso,et al.  A cooperative agent modelling approach for process planning , 2000 .

[9]  Nicolas Spyratos,et al.  On the Semantics of a Semantic Network , 1998, Fundam. Informaticae.

[10]  John M. Usher.  Object oriented approach to feature-based process planning , 1995 .

[11]  D. H. Norrie,et al.  Bidding-based process planning and scheduling in a multi-agent system , 1997 .

[12]  Nicholas R. Jennings.  Agent-Oriented Software Engineering , 1999, MAAMAW.

[13]  Gheorghe Tecuci.  Building Intelligent Agents: An Apprenticeship, Multistrategy Learning Theory, Methodology, Tool and Case Studies , 1998 .

[14]  Gerhard Preuss,et al.  Foundations of Topology: An Approach to Convenient Topology , 2002 .

[15]  Omar López-Ortega.  Design and implementation of an open manufacturing information system to enhance data sharing and exchanging among applications , 2002, Industrial Electronics, 2002. ISIE 2002. Proceedings of the 2002 IEEE International Symposium on.

[16]  Weiming Shen,et al.  MetaMorph II: an agent-based architecture for distributed intelligent design and manufacturing , 2000, J. Intell. Manuf..

[17]  A. Balakrishnan.  Applied Functional Analysis , 1976 .

[18]  Hyacinth S. Nwana,et al.  2 Multi-Agent Systems : Promises and Reality , 1999 .

[19]  Gerhard Preuss,et al.  Foundations of Topology , 2002 .