Abstract
This chapter introduces the ABBPS modeling perspective in Sect. 6.1. Next, Sect. 6.2 explores the main concepts of practical applications and theoretical implications of agent-based simulations, while Sect. 6.3 provides a brief review of the related topics, such as complexity concepts. Finally, Sect. 6.4 describes some advanced features of ABM adopted in the remainder of the book.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Abubakar, A.M., Elrehail, H., Alatailat, M.A., Elçi, A.: Knowledge management, decision-making style and organizational performance. J. Innovation Knowl. 4(2), 104–114 (2019). https://doi.org/10.1016/j.jik.2017.07.003
Amantea, I.A., Di Leva, A., Sulis, E.: A simulation-driven approach to decision support in process reorganization: a case study in healthcare. In: Exploring Digital Ecosystems, pp. 223–235. Springer, Berlin (2020). https://doi.org/10.1007/978-3-030-23665-6_16
Amantea, I.A., Leva, A.D., Sulis, E.: A simulation-driven approach in risk-aware business process management: A case study in healthcare. In: Rango, F.D., Ören, T.I., Obaidat, M.S. (eds.) Proceedings of 8th International Conference on Simulation and Modeling Methodologies, Technologies and Applications, SIMULTECH 2018, Porto, Portugal, July 29–31, 2018, pp. 98–105. SciTePress (2018). https://doi.org/10.5220/0006842100980105
Axelrod, R.: Advancing the art of simulation in the social sciences. In: Simulating social phenomena, pp. 21–40. Springer, Berlin (1997). https://doi.org/10.1002/(sici)1099-0526(199711/12)3:2
Balaji, S., Murugaiyan, M.S.: Waterfall vs. v-model vs. agile: a comparative study on sdlc. Int. J. Inform. Technol. Bus. Manag. 2(1), 26–30 (2012). https://doi.org/10.17950/ijer/v4s4/405
Barrat, A., Barthelemy, M., Vespignani, A.: Dynamical Processes on Complex Networks. Cambridge University Press, Cambridge (2008). https://doi.org/10.1017/CBO9780511791383
Batty, M.: Agent-based models for geographical systems: a review (2019). https://doi.org/10.1007/978-90-481-8927-4. Accessed 15 Jan 2021
Bellifemine, F.L., Caire, G., Greenwood, D.: Developing Multi-Agent Systems with JADE, vol. 7. Wiley, London (2007). https://doi.org/10.1002/9780470058411
Bengio, Y.: Learning deep architectures for AI. Found. Trends Mach. Learn. 2(1), 1–127 (2009). https://doi.org/10.1561/2200000006
Binci, D., Belisari, S., Appolloni, A.: Bpm and change management: an ambidextrous perspective. Bus. Process Manag. J. (2019). https://doi.org/10.1108/BPMJ-06-2018-0158
Boissier, O., Bordini, R.H., Hübner, J.F., Ricci, A., Santi, A.: Multi-agent oriented programming with JaCaMo. Sci. Comput. Program. 78(6), 747–761 (2013). https://doi.org/10.1016/j.scico.2011.10.004
Bolstad, P.: GIS fundamentals: a first text on geographic information systems. Eider (PressMinnesota) (2016)
Bonabeau, E.: Agent-based modeling: Methods and techniques for simulating human systems. Proc. Nat. Acad. Sci. 99(suppl 3), 7280–7287 (2002). https://doi.org/10.1073/pnas.082080899
Bordini, R.H., Hübner, J.F., Wooldridge, M.: Programming multi-agent systems in AgentSpeak using Jason, vol. 8. Wiley, London (2007). https://doi.org/10.1002/9780470061848
Box, G.E.: Science and statistics. J. Am. Stat. Assoc. 71(356), 791–799 (1976). https://doi.org/10.1080/01621459.1976.10480949
Brown, D.G., Riolo, R., Robinson, D.T., North, M., Rand, W.: Spatial process and data models: toward integration of agent-based models and GIS. J. Geograph. Syst. 7(1), 25–47 (2005). https://doi.org/10.1007/s10109-005-0148-5
Buckley, W.: Society as a complex adaptive system. In: Systems Research for Behavioral Science Systems Research, pp. 490–513. Routledge, London (2017). https://doi.org/doi.org/10.4324/9781315130569
Burrough, P.A., McDonnell, R., McDonnell, R.A., Lloyd, C.D.: Principles of Geographical Information Systems. Oxford University Press, Oxford (2015). https://doi.org/10.1111/j.1745-7939.2000.tb01582.x
Caillou, P., Rey Coyrehourq, S., Marilleau, N., Banos, A.: 6—exploring complex models in netlogo. In: Banos, A., Lang, C., Marilleau, N. (eds.) Agent-Based Spatial Simulation with NetLogo, vol. 2, pp. 173–208. Elsevier, Amsterdam (2017). https://doi.org/10.1016/B978-1-78548-157-4.50006-6
Collier, N., North, M.: Repast HPC: a platform for large-scale agent-based modeling. Large-Scale Comput. 81–109 (2012). https://doi.org/10.1002/9781118130506.ch5
Crooks, A., Malleson, N., Manley, E., Heppenstall, A.: Agent-Based Modelling and Geographical Information Systems: A Practical Primer. SAGE Publications Limited (2018). https://doi.org/10.4135/9781473916432.n4
Crooks, A.T., Castle, C.J.: The integration of agent-based modelling and geographical information for geospatial simulation. In: Agent-Based Models of Geographical Systems, pp. 219–251. Springer, Berlin (2012). https://doi.org/10.1007/978-90-481-8927-4_12
Curtis, B., Kellner, M.I., Over, J.: Process modeling. Commun. ACM 35(9), 75–90 (1992)
Dahl, O.J., Nygaard, K.: Simula: an algol-based simulation language. Commun. ACM 9(9), 671–678 (1966)
De Wolf, T., Holvoet, T.: Emergence versus self-organisation: different concepts but promising when combined. In: Brueckner, S.A., Di Marzo Serugendo, G., Karageorgos, A., Nagpal, R. (eds.) Engineering Self-Organising Systems, pp. 1–15. Springer, Berlin (2005). https://doi.org/10.1007/11494676_1
Di Francescomarino, C., Dumas, M., Federici, M., Ghidini, C., Maggi, F.M., Rizzi, W., Simonetto, L.: Genetic algorithms for hyperparameter optimization in predictive business process monitoring. Inform. Syst. 74, 67–83 (2018). https://doi.org/10.1016/j.is.2018.01.003
Di Francescomarino, C., Ghidini, C., Maggi, F.M., Petrucci, G., Yeshchenko, A.: An eye into the future: leveraging a-priori knowledge in predictive business process monitoring. In: International Conference on Business Process Management, pp. 252–268. Springer, Berlin (2017)
Di Leva, A., Sulis, E., De Lellis, A., Amantea, I.A.: Business process analysis and change management: the role of material resource planning and discrete-event simulation. In: Exploring Digital Ecosystems, pp. 211–221. Springer, Berlin (2020). https://doi.org/10.1007/978-3-030-23665-6_15
Dumas, M., La Rosa, M., Mendling, J., Reijers, H.: Fundamentals of Business Process Management, vol. 1, 2nd edn. Springer, Berlin (2018). https://doi.org/10.1007/978-3-662-56509-4
Effken, J.A., Brewer, B.B., Logue, M.D., Gephart, S.M., Verran, J.A.: Using cognitive work analysis to fit decision support tools to nurse managers’ work flow. Int. J. Med. Inform. 80(10), 698–707 (2011). https://doi.org/10.1016/j.ijmedinf.2011.07.003
Eliasson, G.: Modeling the experimentally organized economy: complex dynamics in an empirical micro-macro model of endogenous economic growth. J. Econ. Behav. Organ. 16(1–2), 153–182 (1991). https://doi.org/10.1016/0167-2681(91)90047-2
Farkas, D., Hilton, B., Pick, J., Ramakrishna, H., Sarkar, A., Shin, N.: A tutorial on geographic information systems: a ten-year update. Commun. Assoc. Inform. Syst. 38(1), 9 (2016). https://doi.org/10.17705/1CAIS.03809
Georgeff, M., Pell, B., Pollack, M., Tambe, M., Wooldridge, M.: The belief-desire-intention model of agency. In: International Workshop on Agent Theories, Architectures, and Languages, pp. 1–10. Springer, Berlin (1998). https://doi.org/10.1007/3-540-49057-4_1
Grimm, V., Berger, U., Bastiansen, F., Eliassen, S., Ginot, V., Giske, J., Goss-Custard, J., Grand, T., Heinz, S.K., Huse, G., Huth, A., Jepsen, J.U., Jørgensen, C., Mooij, W.M., Müller, B., Pe’er, G., Piou, C., Railsback, S.F., Robbins, A.M., Robbins, M.M., Rossmanith, E., Rüger, N., Strand, E., Souissi, S., Stillman, R.A., Vabø, R., Visser, U., DeAngelis, D.L.: A standard protocol for describing individual-based and agent-based models. Ecol. Model. 198(1), 115–126 (2006). https://doi.org/doi.org/10.1016/j.ecolmodel.2006.04.023
Grimm, V., Berger, U., DeAngelis, D.L., Polhill, J.G., Giske, J., Railsback, S.F.: The ODD protocol: a review and first update.Ecol. Model. 221(23), 2760–2768 (2010). https://doi.org/10.1016/j.ecolmodel.2010.08.019
Hart, P.E., Nilsson, N.J., Raphael, B.: A formal basis for the heuristic determination of minimum cost paths. IEEE Trans. Syst. Sci. Cybern. 4(2), 100–107 (1968). https://doi.org/10.1109/TSSC.1968.300136
Heppenstall, A.J., Crooks, A.T., See, L.M., Batty, M.: Agent-Based Models of Geographical Systems. Springer, Berlin (2011). https://doi.org/10.1007/978-90-481-8927-4
Holland, J.: Adaptation in natural and artificial systems: an introductory analysis with application to biology. Control and artificial intelligence (1975)
Kaptelinin, V., Nardi, B.A.: Acting with Technology: Activity Theory and Interaction Design. MIT Press, Cambridge (2006). https://doi.org/10.5210/fm.v12i4.1772
Kechagioglou, X., Lemmens, R., Retsios, V.: Sharing geoprocessing workflows with business process model and notation (BPMN). In: Proceedings of the 2019 2nd International Conference on Geoinformatics and Data Analysis, pp. 56–60 (2019). https://doi.org/10.1145/3318236.3318239
Kleijnen, J.P.: Sensitivity analysis and optimization in simulation: design of experiments and case studies. In: Winter Simulation Conference Proceedings, 1995., pp. 133–140. IEEE, IEEE (1995). https://doi.org/10.1109/WSC.1995.478715
Kravari, K., Bassiliades, N.: A survey of agent platforms. J. Artif. Soc. Soc. Simul. 18(1), 11 (2015). https://doi.org/10.18564/jasss.2661
Law, A.M.: Simulation Modeling & Analysis, 5th edn. McGraw-Hill, New York (2015)
Law, A.M.: How to build valid and credible simulation models. In: 2019 Winter Simulation Conference (WSC), pp. 1402–1414. IEEE, Piscataway (2019). https://doi.org/10.1109/WSC40007.2019.9004789
Longley, P.A., Clarke, G.: GIS for Business and Service Planning. Wiley, London (1996). https://doi.org/10.1016/S0969-6989(97)81473-7
Macy, M.W., Willer, R.: From factors to actors: Computational sociology and agent-based modeling. Ann. Rev. Sociol. 28(1), 143–166 (2002). https://doi.org/10.1146/annurev.soc.28.110601.141117
Mansar, S.L., Reijers, H.A.: Best practices in business process redesign: validation of a redesign framework. Comput. Ind. 56(5), 457–471 (2005). https://doi.org/10.1016/j.compind.2005.01.001
Marchiori, M., Possamai, L.: Micro-macro analysis of complex networks. PLoS ONE 10(1), 1–27 (2015). https://doi.org/10.1371/journal.pone.0116670
de Medeiros, A.K.A., Weijters, A.J., van der Aalst, W.: Genetic process mining: an experimental evaluation. Data Mining Knowl. Discovery 14(2), 245–304 (2007). https://doi.org/10.1007/s10618-006-0061-7
Meisel, C., Gross, T.: Adaptive self-organization in a realistic neural network model. Phys. Rev. E 80(6), 061917 (2009). https://doi.org/10.1103/PhysRevE.80.061917
Micolier, A., Taillandier, F., Taillandier, P., Bos, F.: Li-bim, an agent-based approach to simulate occupant-building interaction from the building-information modelling. Eng. Appl. Artif. Intell. 82, 44–59 (2019). https://doi.org/10.1016/j.engappai.2019.03.008
Mitchel, A., et al.: The ESRI Guide to GIS Analysis, vol. 2: Spartial Measurements and Statistics. ESRI Press (2005)
Naylor, T.H., Finger, J.M.: Verification of computer simulation models. Manag. Sci. 14(2), B–92 (1967). https://doi.org/10.1287/mnsc.14.2.B92
Newman, M.E.J.: The structure and function of complex networks. SIAM Rev. 45(2), 167–256 (2003). https://doi.org/10.1137/S003614450342480
North, M.J., Collier, N.T., Ozik, J., Tatara, E.R., Macal, C.M., Bragen, M., Sydelko, P.: Complex adaptive systems modeling with repast simphony. Complex Adapt. Syst. Model. 1(1), 1–26 (2013). https://doi.org/10.1186/2194-3206-1-3
Pal, C., Leon, F., Paprzycki, M., Ganzha, M.: A review of platforms for the development of agent systems. CoRR abs/2007.08961 (2020). https://arxiv.org/abs/2007.08961
Pászto, V., Jürgens, C., Tominc, P., Burian, J.: Spationomy: Spatial Exploration of Economic Data and Methods of Interdisciplinary Analytics. Springer, Berlin (2020). https://doi.org/10.1007/978-3-030-26626-4
Pick, J.B.: Geo-Business: GIS in the Digital Organization. Wiley, London (2008). https://doi.org/10.1002/9780470259955
Rao, A.S.: Agentspeak (l): Bdi agents speak out in a logical computable language. In: European Workshop on Modelling Autonomous Agents in a Multi-Agent World, pp. 42–55. Springer, Berlin (1996)
Sakellariou, I.: Agent based modelling and simulation using state machines. In: SIMULTECH, pp. 270–279. https://doi.org/10.5220/0004164802700279
Sargent, R.G.: Verification and validation of simulation models. J. Simul. 7(1), 12–24 (2013). https://doi.org/10.1109/WSC.2010.5679166
Sawyer, R.K.: Artificial societies: multiagent systems and the micro-macro link in sociological theory. Sociol. Methods Res. 31(3), 325–363 (2003). https://doi.org/10.1177/0049124102239079
Sawyer, R.K., Sawyer, R.K.S.: Social Emergence: Societies as Complex Systems. Cambridge University Press, Cambridge (2005). https://doi.org/10.1017/CBO9780511734892
Sharifi, H., Zhang, Z.: Agile manufacturing in practice-application of a methodology. Int. J. Oper. Prod. Manag. (2001). https://doi.org/10.1108/01443570110390462
Sierhuis, M., Clancey, W.J., Van Hoof, R.J.: Brahms: a multi-agent modelling environment for simulating work processes and practices. Int. J. Simul. Process Model. 3(3), 134–152 (2007). https://doi.org/10.1504/IJSPM.2007.015238
Solé, R.V., Bascompte, J.: Self-Organization in Complex Ecosystems.(MPB-42). Princeton University Press, Princeton (2006). https://doi.org/10.1515/9781400842933
Soon, K.L., Lim, J.M.Y., Parthiban, R., Ho, M.C.: Proactive eco-friendly pheromone-based green vehicle routing for multi-agent systems. Expert Syst. Appl. 121, 324–337 (2019). https://doi.org/10.1016/j.eswa.2018.12.026
Stonedahl, F.J.: Genetic algorithms for the exploration of parameter spaces in agent-based models. Ph.D. Thesis, Northwestern University (2011)
Sulis, E., Terna, P., Di Leva, A., Boella, G., Boccuzzi, A.: Agent-oriented decision support system for business processes management with genetic algorithm optimization: an application in healthcare. J. Med. Syst. 44(9), 1–7 (2020). https://doi.org/10.1007/s10916-020-01608-4
Taillandier, P., Gaudou, B., Grignard, A., Huynh, Q.N., Marilleau, N., Caillou, P., Philippon, D., Drogoul, A.: Building, composing and experimenting complex spatial models with the gama platform. GeoInformatica 23(2), 299–322 (2019). https://doi.org/10.1007/s10707-018-00339-6
Teinemaa, I., Dumas, M., Maggi, F.M., Di Francescomarino, C.: Predictive business process monitoring with structured and unstructured data. In: International Conference on Business Process Management, pp. 401–417. Springer, Berlin (2016). https://doi.org/10.1007/978-3-319-45348-4_23
Tisue, S., Wilensky, U.: NetLogo: A simple environment for modeling complexity. In: International Conference on Complex Systems, vol. 21, pp. 16–21. Boston (2004)
Treiblmayr, M., Tso-Sutter, K.H.L., Krüger, A.: Interfacing business processes and spatial processes. In: Proceedings 2011 IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services, pp. 174–180. IEEE, Piscataway (2011). https://doi.org/10.1109/ICSDM.2011.5969027
Uhrmacher, A.M., Weyns, D.: Multi-Agent Systems: Simulation and Applications. CRC Press (2009). https://doi.org/10.1201/9781420070248
Watkins, C.J., Dayan, P.: Q-learning. Mach. Learn. 8(3-4), 279–292 (1992). https://doi.org/10.1007/BF00992698
Watkins, C.J.C.H.: Learning from Delayed Rewards. King’s College, Cambridge (1989). https://doi.org/10.1201/9781420070248
Whitley, D.: A genetic algorithm tutorial. Stat. Comput. 4(2), 65–85 (1994). https://doi.org/10.1007/BF00175354
Wilensky, U., Rand, W.: An Introduction to Agent-Based Modeling: Modeling Natural, Social, and Engineered Complex Systems with NetLogo. MIT Press, Cambridge (2015). https://doi.org/10.1063/PT.3.2884
Wynn, D.C., Clarkson, P.J.: Process models in design and development. Res. Eng. Design 29(2), 161–202 (2018). https://doi.org/10.1007/s00163-017-0262-7
Zhu, X., Zhu, G., vanden Broucke, S., Recker, J.: On merging business process management and geographic information systems: modeling and execution of ecological concerns in processes. In: International Conference on Geo-Informatics in Resource Management and Sustainable Ecosystem, pp. 486–496. Springer, Berlin (2014). https://doi.org/10.1007/978-3-662-45737-5_48
Zouad, S., Boufaida, M.: An agent-oriented methodology for business process management. In: International Symposium on Business Modeling and Software Design, pp. 287–296. Springer, Berlin (2020). https://doi.org/10.1007/978-3-030-52306-0_19
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2022 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Sulis, E., Taveter, K. (2022). The Agent-Based Business Process Simulation Approach. In: Agent-Based Business Process Simulation. Springer, Cham. https://doi.org/10.1007/978-3-030-98816-6_6
Download citation
DOI: https://doi.org/10.1007/978-3-030-98816-6_6
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-98818-0
Online ISBN: 978-3-030-98816-6
eBook Packages: Computer ScienceComputer Science (R0)