Holonification of a Network of Agents Based on Graph Theory

A multi-agent system consists of a group of interacting autonomous agents. The key problem in such a system is coordination and cooperation, i.e. how to ensure that individual decisions of the agents result in jointly optimal decisions for the overall system. This problem becomes even more serious when the number of the agents is large. Holonic model is an effective method to manage large scale problems. In holonic approaches, the formation of the initial holons is very critical and has a great influence on their performance and effectiveness. In this paper, we use a graph based modelling approach to group a population of agents with a greedy method, driven by a very simple and effective quality measure. The proposed method is evaluated by applying it to an urban traffic problem as a case study and it is shown the proposed method produces better results.

[1]  Christopher J. Hogger,et al.  A Multi-Agent Approach for Intelligent Traffic-Light Control , 2007, World Congress on Engineering.

[2]  Sebastian Rodriguez,et al.  Towards a holonic multiple aspect analysis and modeling approach for complex systems: Application to the simulation of industrial plants , 2007, Simul. Model. Pract. Theory.

[3]  S. E. Schaeffer.  Survey Graph clustering , 2007 .

[4]  Ulrik Brandes,et al.  On Finding Graph Clusterings with Maximum Modularity , 2007, WG.

[5]  Manuela M. Veloso,et al.  Learning of coordination: exploiting sparse interactions in multiagent systems , 2009, AAMAS.

[6]  Sebastian Rodriguez,et al.  Formal Specification of Holonic Multi-Agent Systems Framework , 2005, International Conference on Computational Science.

[7]  Chang-Biau Yang,et al.  Algorithms for the Traffic Light Setting Problem on the Graph M odel , 2007 .

[8]  Huaglory Tianfield,et al.  A new framework of holonic self-organization for multi-agent systems , 2007, 2007 IEEE International Conference on Systems, Man and Cybernetics.

[9]  Sylvain Piechowiak,et al.  A behavioral multi-agent model for road traffic simulation , 2008, Eng. Appl. Artif. Intell..

[10]  Klaus Fischer,et al.  TRANSPORTATION SCHEDULING WITH HOLONIC MAS : THE TELETRUCK APPROACH , 1998 .

[11]  Wen-Xu Wang,et al.  Urban traffic from the perspective of dual graph , 2007, 0710.2992.

[12]  Wen Li,et al.  Step-coordination algorithm of traffic control based on multi-agent system , 2009, Int. J. Autom. Comput..

[13]  George A. Vouros,et al.  Overlay networks for task allocation and coordination in dynamic large-scale networks of cooperative agents , 2007, AAMAS '07.

[14]  Nikos A. Vlassis,et al.  Utile Coordination: Learning Interdependencies Among Cooperative Agents , 2005, CIG.

[15]  Abder Rezak Benaskeur,et al.  Multi-organizational Structures , 2008 .

[16]  Mihaela Ulieru,et al.  Emergent holarchies for e-health applications: a case in glaucoma diagnosis , 2002, IEEE 2002 28th Annual Conference of the Industrial Electronics Society. IECON 02.

[17]  A Koestler,et al.  Ghost in the Machine , 1970 .

[18]  Visit Hirankitti,et al.  An Agent Approach for Intelligent Traffic-Light Control , 2007, First Asia International Conference on Modelling & Simulation (AMS'07).

[19]  Gerhard Weiss,et al.  Multiagent systems: a modern approach to distributed artificial intelligence , 1999 .