Applying process mining approach to support the verification of a multi-agent system

Abstract

Using agent development tools to construct an agent-based system is a well applied approach. However, the development tools usually do not have the function to check the feasibility about the workflow of the agent system during it implementation stage. Therefore, to develop an evaluation approach to analyze the feasibility of a developing agent system such that the improper workflow of an agent system can be found in the early design stage is a necessary task to reduce the risk of implementation.

In this research, a Petri Net (PN) based three-stage evaluation approach was developed.

In the conceptual stage, the pitfall of the current agent system developing process was examined and an improvement analysis process was specified. Then, in the system design stage, an evaluation approach which extracted the process log file from a developing agent system into a PN model in terms of a process mining approach-α algorithm was proposed. This model was simulated in a PN simulation package. The agent system performance was evaluated in terms of analyzing the deadlock phenomena of the PN model. Finally, in the implementation stage, the proposed concept was implemented by using an agent developing tool JADE and a PN simulation tool CPN. An agent-based robotic assembly system was used to examine the possible deadlock of the agent system.

Keywords

Agent-based systems / workflow feasibility / process mining / Petri Nets

References

[1] van der Aalst W.M.P., Weijters A.J.M.M., Maruster L.. Workflow mining: discovering process models from event logs. IEEE Transactions on Knowledge and Data Engineering, 2004, 16(9): 1128-1142.

[2] van der Aalst, W.M.P., Rubin, V., van Dongen, B.F., Kindler, E. & Gunther, C.W. (2006). Process mining: a two-step approach using transition systems and regions. BPM Center Report BPM-06-30. Available via DIALOG. http://wwwis.win.tue.nl/~wvdaalst/BPMcenter/reports.htm

[3] Agrawal, R., Gunopulos, D. & Leymann, F. (1998). Mining process from workflow logs. In: Sixth International Conference on Extending Database Technology, 469–483

[4] Cardid M., Cigolini R., Marco D.D.. Improving supply chain collaboration by linking intelligent agent to CPFR. International Journal of Production Research, 2005, 43(20): 4191-4218.

[5] Chiu M., Lin G.. Collaborative supply chain planning using the artificial neural network approach. Journal of Manufacturing Technology Management, 2004, 15(8): 787-796.

[6] Damm W., Hungar H., Olderog E.R.. Verification of cooperating traffic agents. International Journal of Control, 2006, 79(4): 395-421.

[7] Deen S.M., Jayousi R.. A preference processing model for cooperative agents. Journal of Intelligence Information System, 2006, 126: 115-147.

[8] DeLoach, S.A. (1999). Multiagent systems engineering: A methodology and language for designing agent systems. In: Proceedings of Agent-Oriented Information Systems (AOIS), 45–57

[9] Fan Y., Huang C., Wang Y., Zhang L.. Architecture and operational mechanism of networked manufacturing integrated platform. International Journal of Production Research, 2005, 43(12): 2615-2629.

[10] Forget P., D’Amours S., Frayret J.-M.. Multi-behavior agent model for planning in supply chains: an application to the lumber industry. Robotics and Computer-Integrated Manufacturing, 2008, 24(5): 664-679.

[11] Kowalczyk, R., Franczyk, B., Speck, A., Braun, P., Eismann, J. & Rossak, W. (2002). Intermarket-towards intelligent mobile agent e-marketplaces. In: Proceedings of 9th Annual IEEE International Conference and Workshop on Engineering of Computer-Based Systems, 268–275

[12] Kuk S.H., Kim H.S., Lee J.K., Han S., Park S.W.. An e-engineering framework based on service-oriented architecture and agent technologies. Computers in Industry, 2008, 59(9): 923-935.

[13] Lau J.S.K., Huang G.Q., Mak K.L., Liang L.. Distributed project scheduling with information sharing in supply chains, Part I: an agent-based negotiation model. International Journal of Production Research, 2005, 43(22): 4813-4838.

[14] Lau J.S.K., Huang G.Q., Mak K.L., Liang L.. Agent-based modeling of supply chains for distributed scheduling. IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans, 2006, 136(5): 847-861.

[15] Li Y., Jian J., Yan R., Liao W.. Aircraft tooling collaborative design based on multi-agent and PDM. Concurrent Engineering, 2009, 17(2): 139-146.

[16] Lin F.R., Chang K.Y.. A multi-agent framework for automated online bargaining. IEEE Intelligent Systems, 2001, 16(4): 41-47.

[17] Lu T.P., Chang T.M., Yih Y.. Production control framework for supply chain management-an application in the elevator manufacturing industry. International Journal of Production Research, 2005, 43(20): 4219-4233.

[18] Nwana H., Ndumu D., Lee L., Collis J.. ZEUS: a tool-kit for building distributed multi-agent systems. Journal of Applied Artificial Intelligence, 1999, 13: 187-208.

[19] Rozinat A., De Medeiros A.K.A., Gunther C.W., Weijters A.J.M.M., van der Aalst W.M.P.. The need for a process mining evaluation framework in research and practice. Lecture Notes in Computer Science, 2008, 4928: 84-89.

[20] Shen W., Hao Q., Yoon H.J., Norrie D.H.. Applications of agent-based systems in intelligent manufacturing: an updated review. Advanced Engineering Informatics, 2006, 20: 415-431.

[21] Schoop R., Neubert R., Colombo A.W.. A multiagent-based distributed control platform for industrial flexible production systems. IECON’01, The 27th Annual Conference of the IEEE Industrial Electronics Society, 2001, 1: 279-284.

[22] Stadtler H.. Supply chain management and advanced planning-basics, overview and challenges. European Journal of Operational Research, 2005, 163(3): 575-588.

[23] Wen L., Wang J., Sun J.G.. Detecting implicit dependencies between tasks from event logs. Lecture Notes in Computer Science, 2006, 3841: 591-603.

[24] Weijters A.J.M.M., van der Aalst W.M.P.. Rediscovering workflow models from event-based data. Integrated Computer-Aided Engineering, 2003, 10(2): 151-162.

[25] Wooldridge M., Jennings R., Kinny D.. The Gaia methodology for agent-oriented analysis and design. Autonomous Agents and Multi-Agent Systems, 2000, 3: 285-312.

[26] Zhang W.J., Xie S.Q.. Agent technology for collaborative process planning: a review. International Journal of Advanced Manufacturing Technology, 2007, 32: 315-325.

[27] Zhou M.. Petri Net Synthesis for Discrete Event Control of Manufacturing Systems, 1993, Massachusetts: Kluwer Academic Publishers.