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Formal Modeling towards a Dynamic Organization of Multi-agent Systems Using Communicating X-machine and Z-notation


Affiliations
1 Faculty of Information Technology, University of Central Punjab Lahore, Pakistan
2 Department of Computer Sciences, COMSATS Institute of Information Technology, Attock, Pakistan
3 Department of Computer Science, College of Computer Science and Information Technology, King Faisal University, Al Hassa, Saudi Arabia
 

The real world is a dynamic place where things change in an unexpected way. Software must be able to adapt these changes to work efficiently in the real world. Modeling of the multi-agent system implies modeling of the agent's dynamic structure and behavior, including their ability to communicate with other agent of the systems and dynamically organize their formation over time. In this research we used two different formal methods, communicating stream Xmachine and Z notation, for writing the formal specification of multi-agent systems with a dynamic structure and behavior. Both the modeling techniques possess different characteristics which are discussed through the modeling process of multi-agent system. A case study of biologically inspired multi-agent system is taken to illustrate the proposed modeling approach.

Keywords

Communicating Stream X-machine, Z Notation, Multi-agent System, Formal Modeling
User

  • Akbari OZ (2010) A Survey of agent-oriented software engineering paradigm: Towards its industrial acceptance. J. Comput. Engg. Res. 1(2), 14-28.

  • Ali G and Zafar NA (2010) Formal modeling of multiagent systems using communicating stream X-Machine and Z Notation. Proce. Intl. Conf. Intelligence & Info. Technol.pp: 523-527.

  • Benerecetti M, Giunchiglia F and Serafini L (1998) A model checking algorithm for multi-agent systems. Proce. 5thIntl. Workshop Intelligent Agents V, Agent Theories, Architec. & Languages.pp: 163-176.

  • Bordini RH, Dastani M and Winikoff M (2008) Current issues in multi-agent systems development. Proce. 7thInt. Joint Conf.Autonomous Agents & Multiagent Sys., ACM.pp: 233-240.

  • Celaya JR, Desrochers AA and Graves RJ (2009) Modeling and analysis of multi-agent systems using petri nets. J. Comput. 4(10), 981-996.

  • Chaibdraa B and Dignum F (2002) Trends in agent communication language. Comput. Intelligence. 18(2), 89-101.

  • Deloach SA(1999) Multiagent systems engineering. Methodol. & Language For Desig. Agent Sys., Agent- Oriented Info. Sys.,Seattle WA, USA.

  • Eleftherakis G, Kefalas P, Sotiriadou A and Kehris E (2005) Modeling biology inspired reactive agents using xmachine. Proc. World Acad. Sci., Engg.& Technol.pp: 63- 66.

  • Goodwin R (1993) Formalizing properties of agents. CMU-CS.pp: 93-159.

  • Kefalas P, Stamatopoulou L and Gheorghe M (2005) A formal modelling framework for developing multi-agent systems with dynamic structure and behaviour. Proc.4thInt. Central & Eastern Europ. Conf. Multi-Agent Sys. & Appl. pp:122-131.

  • Khalesian M and Delavar MR (2008) A multi-agent based traffic network micro-simulation using spatio-temporal GIS. Intl. Archives Photogrammetry, Remote Sensing & Spatial Info. Sci. 12(7), 31-35.

  • Khan SAand Zafar NA (2011) Improving moving block railway system using fuzzy multi-agent specification language.Int. J. Innovative Computing, Info.& Control. 7(7(B)), 4517-4534.

  • Khan SA, Zafar NA and Ahmad F (2011b) Petri net modeling of railway crossing system using fuzzy brakes.Intl. J. Physical Sci. 6(14), 3389-3397.

  • Luck M, Griffiths N and d’Inverno M (1997) From agent theory to agent construction: a case study. Proc. 3rd Int. Workshop Agent Theories, Architec. & Languages.pp: 49-63.

  • Marzougui B, Hassine K and Barkaoui K (2010) A New formalism for modeling a multi agent systems: agent petri nets. J. Software Eng.& Appl.3, 1118-1124.

  • Mitkas P (2005) Knowledge discovery for training intelligent agents: methodology. tools and applications.Autonomous Intelligent Sys., Agents &Data Mining, Lecture Notes in Comput. Sci.3505, 2-18.

  • Odell J, Parunak HVD and Bauer B (2000) Extending UML for agents. Proce. Agent Oriented Info. Sys. Workshop (AOIS) 17th National Conf. Artificial Intelligence. pp: 3-17.

  • Rao AS and Georgeff M (1995) BDI-agents: from theory to practice. Proce. 1stInt. Conf. Multiagent Sys.pp:312- 319.

  • Spivey JM (1989)The znotation.Reference Manual. Englewood Cliffs, NJ, Prentice-Hall.

  • StamatopoulouI, Gheorghe Mand Kefalas P (2005) Modelling of dynamic organization of biology-inspired multi-agent systems with communicating x-machines and p systems. 5th Workshop in Membrane Computing, Springer-Verlag, Berlin, Milan Italy. 3365,389-403.

  • Winikoff M (2009) Future Directions for agent-based software engineering. Int. J. Agent-Oriented Software Eng. 3(4), 402-410.

  • Wooldridge M and Ciancarini P(2000) Agent-oriented software engineering: the state of the art.1stInt. Workshop on Agent-Oriented Software Eng.pp:1-28.

  • Xudong H, Huiqun Y and Ding Y (2006) Formal methods for specifying and analyzing complex software systems. Modern Formal Methods & Appl., Springer. pp: 123-150.

  • StamatopoulouI,Sakellariou I,Kefalas P and Eleftherakis G (2007) Formal modeling for in-silico experiments with social insect colonies.Proc.11thPanhellenic Conf. Info.pp: 79-89.

  • Zafar NA and Ali G (2010) Transformation of X-machine to Z notation enhancing modeling power for distributed systems. Proc. Int. Conf. Software Engg. Theory & Practice. pp: 54-61.

  • Zafar NA, Khan SA and Araki K (2012) Towards the safety properties of moving block railway interlocking system. Int. J. Innovative Comput., Info & Control. (Accepted) 8(7).

  • Zhao Cand Wang L (2009) Computational modeling of complex systems: case study in real world. Proc. 9th Int. Conf. Hybrid Intelligent Sys.pp: 33-38.


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  • Formal Modeling towards a Dynamic Organization of Multi-agent Systems Using Communicating X-machine and Z-notation

Abstract Views: 502  |  PDF Views: 138

Authors

Ghulam Ali
Faculty of Information Technology, University of Central Punjab Lahore, Pakistan
Sherafzal Khan
Department of Computer Sciences, COMSATS Institute of Information Technology, Attock, Pakistan
Nazir Ahmad Zafar
Department of Computer Science, College of Computer Science and Information Technology, King Faisal University, Al Hassa, Saudi Arabia
Farooq Ahmad
Faculty of Information Technology, University of Central Punjab Lahore, Pakistan

Abstract


The real world is a dynamic place where things change in an unexpected way. Software must be able to adapt these changes to work efficiently in the real world. Modeling of the multi-agent system implies modeling of the agent's dynamic structure and behavior, including their ability to communicate with other agent of the systems and dynamically organize their formation over time. In this research we used two different formal methods, communicating stream Xmachine and Z notation, for writing the formal specification of multi-agent systems with a dynamic structure and behavior. Both the modeling techniques possess different characteristics which are discussed through the modeling process of multi-agent system. A case study of biologically inspired multi-agent system is taken to illustrate the proposed modeling approach.

Keywords


Communicating Stream X-machine, Z Notation, Multi-agent System, Formal Modeling

References





DOI: https://doi.org/10.17485/ijst%2F2012%2Fv5i7%2F30494