A hierarchical Markov model to understand the behaviour of agents in business processes

Lecture Notes in Business Information Processing

Volumn 132 LNBIP, Issue , 2013, Pages 150-161

  Ferreira, Diogo R ^a   Szimanski, Fernando ^b   Ralha, Célia Ghedini ^b  

^a INSTITUTO SUPERIOR TÉCNICO   (Portugal)

^b UNIVERSITY OF BRASILIA   (Brazil)

Author keywords

Agent Based Simulation; Agent Object Relationship (AOR); Expectation Maximization; Markov Models; Process Mining

Indexed keywords

DATA MINING; ENTERPRISE RESOURCE MANAGEMENT; MAXIMUM PRINCIPLE;

AGENT BASED SIMULATION; AGENT OBJECT RELATIONSHIPS; EXPECTATION - MAXIMIZATIONS; MARKOV MODEL; PROCESS MINING;

MARKOV PROCESSES;

EID: 84873130906     PISSN: 18651348     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-3-642-36285-9_16     Document Type: Conference Paper

References (15)

1. van der Aalst, W.M.P.: Process Mining: Discovery, Conformance and Enhancement of Business Processes. Springer (2011)
2. Greco, G., Guzzo, A., Pontieri, L.: Mining Hierarchies of Models: From Abstract Views to Concrete Specifications. In: van der Aalst, W.M.P., Benatallah, B., Casati, F., Curbera, F. (eds.) BPM 2005. LNCS, vol. 3649, pp. 32-47. Springer, Heidelberg (2005)
3. Günther, C.W., van der Aalst, W.M.P.: Fuzzy Mining-Adaptive Process Simplification Based on Multi-perspective Metrics. In: Alonso, G., Dadam, P., Rosemann, M. (eds.) BPM 2007. LNCS, vol. 4714, pp. 328-343. Springer, Heidelberg (2007)
4. Günther, C.W., Rozinat, A., van der Aalst, W.M.P.: Activity Mining by Global Trace Segmentation. In: Rinderle-Ma, S., Sadiq, S., Leymann, F. (eds.) BPM 2009. LNBIP, vol. 43, pp. 128-139. Springer, Heidelberg (2010)
5. Bose, R.P.J.C., Verbeek, E.H.M.W., van der Aalst, W.M.P.: Discovering Hierarchical Process Models Using ProM. In: Nurcan, S. (ed.) CAiSE Forum 2011. LNBIP, vol. 107, pp. 33-48. Springer, Heidelberg (2012)
6. Wooldridge, M., Jennings, N.R.: Intelligent agents: Theory and practice. Knowledge Engineering Review 10(2), 115-152 (1995)
7. Veiga, G.M., Ferreira, D.R.: Understanding Spaghetti Models with Sequence Clustering for ProM. In: Rinderle-Ma, S., Sadiq, S., Leymann, F. (eds.) BPM 2009 Workshops. LNBIP, vol. 43, pp. 92-103. Springer, Heidelberg (2010)
8. Dempster, A.P., Laird, N.M., Rubin, D.B.: Maximum likelihood from incomplete data via the EM algorithm. Journal of the Royal Statistical Society 39(1), 1-38 (1977)
9. McLachlan, G.J., Krishnan, T.: The EM Algorithm and Extensions. Wiley Series in Probability and Statistics. Wiley-Interscience (2008)
10. Bonabeau, E.: Agent-based modeling: Methods and techniques for simulating human systems. PNAS 99(suppl. 3), 7280-7287 (2002)
11. Davidsson, P., Holmgren, J., Kyhlb̈ack, H., Mengistu, D., Persson, M.: Applications of Agent Based Simulation. In: Antunes, L., Takadama, K. (eds.) MABS 2006. LNCS (LNAI), vol. 4442, pp. 15-27. Springer, Heidelberg (2007)
12. Railsback, S.F., Lytinen, S.L., Jackson, S.K.: Agent-based simulation platforms: Review and development recommendations. Simulation 82(9), 609-623 (2006)
13. Wagner, G.: AOR Modelling and Simulation: Towards a General Architecture for Agent-Based Discrete Event Simulation. In: Giorgini, P., Henderson-Sellers, B., Winikoff, M. (eds.) AOIS 2003. LNCS (LNAI), vol. 3030, pp. 174-188. Springer, Heidelberg (2004)
14. Wagner, G., Nicolae, O., Werner, J.: Extending discrete event simulation by adding an activity concept for business process modeling and simulation. In: Proceedings of the 2009 Winter Simulation Conference, pp. 2951-2962 (2009)
15. Nicolae, O., Wagner, G., Werner, J.: Towards an Executable Semantics for Activities Using Discrete Event Simulation. In: Rinderle-Ma, S., Sadiq, S., Leymann, F. (eds.) BPM 2009 Workshops. LNBIP, vol. 43, pp. 369-380. Springer, Heidelberg (2010)