A multi-agent system is a useful modeling architecture in business process modeling in the sense that we can naturally implement participants in a real company with software agents. However, analyzing and interpreting the simulation results of multi-agent models tends to be difficult due to the inherent complexity of the models. In this regard, another discipline—process mining—is useful for such purposes because it has demonstrated its usefulness in analyzing real processes. In this article, our aim is to combine these two disciplines for exploitation in business process modeling and simulation; we extend a multi-agent-based business simulator named Multi-Agent system with Resource-Event-Agent ontology (MAREA) to be able to be analyzed by means of process mining techniques. To this end, we formalize the abstract multi-agent architecture of MAREA and establish its relationship to process mining by defining how execution of a multi-agent system can be recorded as an event log, which is later analyzed by process mining techniques. Based on this definition, we implement functionality to extract event logs from simulation runs in MAREA. For demonstration, we implement a model of a generic trading company in MAREA and perform process structure verification and social network analyzes by means of process mining techniques.
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Readers may notice that Fig. 1 shows a ‘Sales order’ going to ERP rather than directly to the Accountant. Because ERP is not an agent, it does not receive messages. Therefore, we set the accountant as the receiver of this message. This message serves as the ‘signal’ that the company ERP has modified as a result of the ‘Sales quote acceptance.’
This is because ProM associates with each edge the frequency of the cases where the agents are working together.
Aris (2000) ARIS—architecture of integrated systems. Workflow management within the ARIS framework. http://www.pera.net/Methodologies/ARIS/ARIS.html. Accessed 1 March, 2017
Barnett M (2003) Modeling and simulation in business process management. http://news.bptrends.com/publicationfiles/11-03%20WP%20Mod%20Simulation%20of%20BPM%20-%20Barnett-1.pdf. Accessed 1 March, 2017
Bellifemine F, Caire G, Poggi A, Rimassa G (2003) JADE a White Paper, TILAB exp ‘in search of innovation’, Vol. 3, No. 3, http://jade.tilab.com/papers/2003/WhitePaperJADEEXP.pdf. Accessed 1 March, 2017
BPMN (2011) Business process model and Notation, version 2.0. http://www.omg.org/spec/BPMN/2.0/PDF/. Accessed 1 March, 2017
Bucki R, Suchanek P (2012) The method of logistic optimization in e-commerce. J Univers Comput Sci 18(10):1238–1258
Cabac L, Knaak N, Moldt D, Rolke H (2006) Analysis of multi-agent interactions with process mining techniques. In: Fischer K, Timm IJ, Andre E, Zhong N (eds) MATES 2006, vol 4196. Lecture notes in computer science. Springer, Berlin, pp 12–23
Davenport T (1992) Process innovation: re-engineering work through information technology. Harvard Business School Press, Boston
de Medeiros AKA, van der Aalst WMP, Weijters AJMM (2003) Workflow mining: current status and future directions. In: Meersman R, Tari Z, Schmidt DC (eds) On the move to meaningful internet systems 2003: CoopIS, DOA, and ODBASE, vol 2888. Lecture notes in computer science. Springer, Berlin, pp 389–406
Dunn CL, Cherrington OJ, Hollander AS (2004) Enterprise information systems: a pattern based approach. McGraw-Hill, New York
Ericsson HE, Penker M (2000) Business modeling with UML: business patterns at work. Wiley, New York
FIPA (2005) FIPA: Foundation for Intelligent Physical Agents. http://www.fipa.org
Gailly F, Poels G (2007) Towards ontology-driven information systems: redesign and formalization of the REA ontology. In: Witold A (ed) Business information systems, 10th International Conference, BIS 2007, vol 4439. Lecture notes in computer science. Springer, Berlin, pp 245–259
Gordijn J, Akkermans J (2002) Value-based requirements engineering exploring innovative e-commerce ideas. Requir Eng 8(2):114–134
Gries M, Kulkarni C, Sauer C, Keutzer K (2003) Comparing analytical modeling with simulation for network processors: a case study. In: Proceedings of the conference on design, automation and test in Europe: designers’ forum - Volume 2 (DATE '03), vol 2. IEEE Computer Society, Washington, DC, pp 20256–20261
Halpern J (2003) Reasoning about uncertainty. MIT Press, Cambridge, MA
Hruby P (2006) Model-driven design using business patterns. Springer, Berlin
Ito S, Vymetal D (2013) The formal REA model at the operational level. Appl Ontol 8(4):275–300
Liu Y, Triverdi S (2006) Survivability quantification: the analytical modeling approach. Int J Perform Eng 2(1):29–44
Macal C, North MJ (2006) Tutorial on agent-based modeling and simulation Part 2: How to model with agents. In: Perrone F, Lawson B, Liu J, Wieland F (ed) Proceedings of the 2006 Winter simulation conference. IEEE, Piscataway NJ, pp 73–83
McCarthy WE (1982) The REA accounting model: a generalized framework for accounting systems in a shared data environment. Acount Rev 57(3):554–578
McFarland DA, Gomez CJ (2014) Organizational analysis. http://service.sipx.com/service/php/inspect_document.php?id=x-06fd656e-b146-11e3-b4ce-22000a90058c. Accessed 1 March, 2017
Odell J (2010) Agent technology: an overview. http://www.jamesodell.com/Agent_Technology-An_Overview.pdf. Accessed 1 March, 2017
Pechoucek M, Marik V (2008) Industrial deployment of multi-agent technologies: review and selected case studies. Auton Agent Multi-AG 17(3):397–431
Rozinat A, Zickler S, Veloso M, van der Aalst WMP, McMillen C (2009) Analyzing multi-agent activity logs using process mining techniques. Springer Trac Adv Ro 8:251–260
Slaninova K (2014) User behavioral patterns and reduced user profiles extracted from log files. In: 13th International Conference on Intelligent Systems Design and Applications. IEEE, Piscataway NJ, pp 289–294
Slaninova K, Martinovic J, Sperka R, Drazdilova P (2013) Extraction of agent groups with similar behavior based on agent profiles. In: Saeed K, Chaki R, Cortesi A, Wierzchon S (ed) 12th IFIP TC8 international conference on Computer Information Systems and Industrial Management Applications (CISIM), vol 8104, Lecture notes in computer science. Springer, Berlin, pp 348–357
Sperka R, Spisak M, Slaninova K, Martinovic J, Drazdilova P (2013) Control loop model of virtual company in BPM simulation. In: Snasel V, Abraham A, Corchado ES (ed) 7th international conference, SOCO’12, vol 188. Advances in intelligent systems and computing. Springer, Berlin, pp 515–524
Suchanek P, Vymetal D (2011) Security and disturbances in e-commerce systems. In: Kocourek A (ed) 10th international conference Liberec economic forum. Technical University of Liberec, Liberec, pp 580–589
van der Aalst WMP (1998) The application of petri nets to workflow management. J Circuit Syst Comput 8(1):21–66
van der Aalst WMP (2004) Business process management: a personal view. Bus Process Manag J 10(2):5
van der Aalst WMP (2011) Process mining. discovery, conformance and enhancement of business processes. Springer, Berlin
van der Aalst WMP (2016) Process mining. Data science in action, vol 2. Springer, Berlin
van der Aalst WMP et al. (2009) Process mining manifesto. IEEE task force for process mining. http://www.win.tue.nl/ieeetfpm/lib/exe/fetch.php?media=shared:process_mining_manifesto-small.pdf. Accessed 1 March, 2017
van der Aalst WMP, Weijters AJMM, Maruster L (2004) Workflow mining: discovering process models from event logs. IEEE T Knowl Data Eng 16(9):1128–1142
van der Aalst WMP, Reijers HA, Song M (2005) Discovering social networks from event logs. Comput Support Coop Work 14(6):549–593
van Dongen B, van Luin J, Verbeek E (2006) Process mining in a multi-agent auctioning system. In: Moldt, D (ed) Proceedings of the 4th International Workshop on Modelling of Objects, Components, and Agents, pp 145–160
Verbeek E, Buijs JCAM, van Dongen BF, van der Aalst WMP (2010) ProM 6: the process mining tooklit. In: Rosa ML (ed) Proceedings of BPM Demonstration Track 2010, CEUR Workshop Proceedings, pp 34–39
Vymetal D, Ito S (2016) The formalization of a generic trading company model using software agents as active elements. Working Paper in Interdisciplinary Economics and Business Research no 29. Silesian University in Opava, School of Business Administration in Karvina
Vymetal D, Jezek F (2014) Demand function and its role in a business simulator. J Adv Res Manag 5(1):41–47
Vymetal D, Schoeller C (2012) MAREA: multi-agent REA-based business process simulation framework. In: Vymetal D, Suchanek P (ed) Conference proceedings of the international scientific conference ICT for competitiveness. Silesian University in Opava, School of Business Administration in Karvina, Karvina, pp 301–310
Vymetal D, Sperka R (2013) Virtual company simulation for distance learning. In: Hruby M (ed) Distance learning simulation and communication proceedings. Univerzita obrany Brno, Brno, pp 189–197
Vymetal D, Sperka R (2014) MAREA—from an agent simulation application to the social network analysis. Procedia Comput Sci 35:1416–1425
Weigand H, Elsas P (2012) Model-based auditing using REA. Int J Account Inf Syst 13(3):287–310
Winikoff M (2010) Assurance of agent systems: what role should formal verification play? In: Dastani M, Hindriks K, Meyer JJ (eds) Specification and verification of multi-agent systems. Springer, Boston, MA
Wooldridge M (2009) MultiAgent systems: an introduction, 2nd edn. Wiley, Chichester
This article was supported by the research project ‘Strengthening international cooperation in the area of science, research and education’, which is financed from the budget of the Moravian and Silesian Region (MSK), Czech Republic, Contract No. 01204/2016/RRd.
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Ito, S., Vymětal, D., Šperka, R. et al. Process mining of a multi-agent business simulator. Comput Math Organ Theory 24, 500–531 (2018). https://doi.org/10.1007/s10588-018-9268-6
- Business process modeling
- Business process simulation
- Multi-agent system
- Process mining