A network inference tool for JADE-based systems

This article describes the first version of a tool designed to infer the network characteristics of JADE-based multiagent systems. The rationale behind the tool is that systems in general and multiagent system in particular, often have some hidden dynamics that contribute to the emergence of desired and undesired characteristics. Traditional sniffing tools simply display the message exchange. The presented tool goes therefore beyond simple message sniffing and infers the agents' network based on the ongoing interactions and codifies it a format suitable for further processing in specialized network analysis tools. In particular the prosped tool identifies the most frequently used communication links and the messages associated with them. To demonstrate the behavior of the tool an exploratory system based on the Evolvable Production System paradigm is discussed and analyzed.

[1]  Luis Ribeiro,et al.  Exploring the network dimension of diagnosis in Evolvable Production Systems , 2010, 2010 IEEE 15th Conference on Emerging Technologies & Factory Automation (ETFA 2010).

[2]  Charles M. Macal,et al.  Tutorial on agent-based modelling and simulation , 2005, Proceedings of the Winter Simulation Conference, 2005..

[3]  A. Tharumarajah,et al.  Comparison of the bionic, fractal and holonic manufacturing system concepts , 1996 .

[4]  Hossein Sharifi,et al.  Agile manufacturing in practice ‐ Application of a methodology , 2001 .

[5]  Jirí Kubalík,et al.  Clustering Methods for Agent Distribution Optimization , 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[6]  Mauro Onori,et al.  The IDEAS project: plug & produce at shop‐floor level , 2012 .

[7]  Luc Bongaerts,et al.  Reference architecture for holonic manufacturing systems: PROSA , 1998 .

[8]  Douglas H. Norrie,et al.  Agent-Based Systems for Intelligent Manufacturing: A State-of-the-Art Survey , 1999, Knowledge and Information Systems.

[9]  Mauro Onori,et al.  Bio-inspired Self-Organising Methodologies for Production Emergence , 2013, 2013 IEEE International Conference on Systems, Man, and Cybernetics.

[10]  Luis Ribeiro,et al.  A structural analysis of emerging production systems , 2012, IEEE 10th International Conference on Industrial Informatics.

[11]  J. Bessant,et al.  The manufacturing strategy‐capabilities links in mass customisation and agile manufacturing – an exploratory study , 2003 .

[12]  Giovanna Di Marzo Serugendo,et al.  Concepts in complexity engineering , 2011, Int. J. Bio Inspired Comput..

[13]  Andrew Reeson,et al.  Agent‐based modeling in ecological economics , 2010, Annals of the New York Academy of Sciences.

[14]  Paul Windrum,et al.  Empirical Validation of Agent-Based Models: Alternatives and Prospects , 2007, J. Artif. Soc. Soc. Simul..

[15]  Xin-She Yang,et al.  Firefly Algorithms for Multimodal Optimization , 2009, SAGA.

[16]  Nicholas R. Jennings,et al.  Intelligent agents: theory and practice , 1995, The Knowledge Engineering Review.

[17]  Hendrik Van Brussel,et al.  Towards the design of autonomic nervousness handling in holonic manufacturing execution systems , 2007, 2007 IEEE International Conference on Systems, Man and Cybernetics.

[18]  Michael Wooldridge,et al.  Intelligent agents: theory and practice The Knowledge Engineering Review , 1995 .

[19]  Dias Ferreira João,et al.  Bio-Inspired Self-Organisation in Evolvable Production Systems , 2013 .