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Agents and Organization Studies

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Agent-Based Business Process Simulation
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Abstract

The notion of agent is one of the most relevant concepts in computer science, within its sub-disciplines of artificial intelligence and information systems. In this chapter, we introduce the main definitions of the concept in the computer science literature. We mention the idea of individual-based modeling. To better understand the topic, we propose an exploration of a database of academic research articles, with a survey of recent trending topics. Adopting “agent” and “business” as keywords, we consider abstracts of scientific articles from the last 20 years. We also report on a semantic graph analysis performed by us to explore the most frequent co-occurring concepts by using network metrics and clustering.

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References

  1. Agha, G.A.: ACTORS—A Model of Concurrent Computation in Distributed Systems. MIT Press Series in Artificial Intelligence. MIT Press, Cambridge (1990). https://doi.org/10.7551/mitpress/1086.001.0001

    Google Scholar 

  2. Agostinelli, S., Marrella, A., Mecella, M.: Research challenges for intelligent robotic process automation. In: Francescomarino, C.D., Dijkman, R.M., Zdun, U. (eds.) Business Process Management Workshops—BPM 2019 International Workshops, Vienna, Austria, September 1-6, 2019, Revised Selected Papers. Lecture Notes in Business Information Processing, vol. 362, pp. 12–18. Springer (2019). https://doi.org/10.1007/978-3-030-37453-2_2

  3. Amores, D., Vasardani, M., Tanin, E.: Early detection of herding behaviour during emergency evacuations. In: Winter, S., Griffin, A., Sester, M. (eds.) 10th International Conference on Geographic Information Science, GIScience 2018, August 28–31, 2018, Melbourne, Australia. LIPIcs, vol. 114, pp. 1:1–1:15. Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2018). https://doi.org/10.4230/LIPIcs.GISCIENCE.2018.1

  4. Arazy, O., Woo, C.C.: Analysis and design of agent-oriented information systems. Knowl. Eng. Rev. 17(3), 215–260 (2002). https://doi.org/10.1017/S0269888902000450

    Article  Google Scholar 

  5. Arel, I., Liu, C., Urbanik, T., Kohls, A.G.: Reinforcement learning-based multi-agent system for network traffic signal control. IET Intell. Trans. Syst. 4(2), 128–135 (2010). https://doi.org/10.1049/iet-its.2009.0070

    Article  Google Scholar 

  6. Badue, C., Guidolini, R., Carneiro, R.V., Azevedo, P., Cardoso, V.B., Forechi, A., Jesus, L., Berriel, R., Paixão, T.M., Mutz, F., et al.: Self-driving cars: a survey. Expert Syst. Appl. 113816 (2020). https://doi.org/10.1016/j.eswa.2020.113816

  7. Bai, Q., Ren, F., Fujita, K., Zhang, M., Ito, T.: Multi-agent and Complex Systems. Springer, Berlin (2017). https://doi.org/10.1007/978-981-10-2564-8

  8. Baldoni, M., Baroglio, C., Boissier, O., May, K.M., Micalizio, R., Tedeschi, S.: Accountability and responsibility in agent organizations. In: International Conference on Principles and Practice of Multi-Agent Systems, pp. 261–278. Springer, Berlin (2018). https://doi.org/10.1007/978-3-030-03098-8

  9. Bastian, M., Heymann, S., Jacomy, M.: Gephi: An open source software for exploring and manipulating networks. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 3 (2009). https://doi.org/10.13140/2.1.1341.1520

  10. Bird, S., Klein, E., Loper, E.: Natural Language Processing with Python: Analyzing Text with the Natural Language Toolkit. O’Reilly, Beijing (2009). http://my.safaribooksonline.com/9780596516499

    MATH  Google Scholar 

  11. Bojarski, M., Del Testa, D., Dworakowski, D., Firner, B., Flepp, B., Goyal, P., Jackel, L.D., Monfort, M., Muller, U., Zhang, J., et al.: End to end learning for self-driving cars (2016). arXiv preprint arXiv:1604.07316. https://doi.org/10.1109/ICCE-Berlin.2018.8576190

  12. 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

    Article  Google Scholar 

  13. Bresciani, P., Perini, A., Giorgini, P., Giunchiglia, F., Mylopoulos, J.: Tropos: an agent-oriented software development methodology. Auton. Agents Multi-Agent Syst. 8(3), 203–236 (2004). https://doi.org/10.1023/B:AGNT.0000018806.20944.ef

    Article  Google Scholar 

  14. Bubenko, J., Kirikova, M.: “worlds” in requirements acquisition and modelling. DSV (1994)

    Google Scholar 

  15. Burt, R.S.: Structural Holes: The Social Structure of Competition. Harvard University Press, Cambridge (1992)

    Book  Google Scholar 

  16. Bösser, T.: Autonomous agents. In: Wright, J. (ed.) International Encyclopedia of the Social & Behavioral Sciences, pp. 1002–1006. Elsevier, Amsterdam (2015). https://doi.org/10.1016/B0-08-043076-7/00534-9

    Google Scholar 

  17. Cuevas, E.: An agent-based model to evaluate the covid-19 transmission risks in facilities. Comput. Biol. Med. 121, 103827 (2020). https://doi.org/10.1016/j.compbiomed.2020.103827

    Article  Google Scholar 

  18. Dhesi, G., Ausloos, M.: Modelling and measuring the irrational behaviour of agents in financial markets: Discovering the psychological soliton. Chaos Solitons Fractals 88, 119–125 (2016). https://doi.org/10.1016/j.chaos.2015.12.015

    Article  MathSciNet  Google Scholar 

  19. Dignum, V., Dignum, F.: Agents are dead. long live agents! In: Seghrouchni, A.E.F., Sukthankar, G., An, B., Yorke-Smith, N. (eds.) Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, AAMAS ’20, Auckland, New Zealand, May 9–13, 2020, pp. 1701–1705. International Foundation for Autonomous Agents and Multiagent Systems (2020). https://dl.acm.org/doi/abs/10.5555/3398761.3398957

  20. Dignum, V., Gilbert, N., Wellman, M.P.: Introduction to the special issue on autonomous agents for agent-based modeling. Auton. Agents Multi-Agent Syst. 30(6), 1021–1022 (2016). https://doi.org/10.1007/s10458-016-9345-5

    Article  Google Scholar 

  21. Fortino, G., Guerrieri, A., Russo, W.: Agent-oriented smart objects development. In: Proceedings of the 2012 IEEE 16th International Conference on Computer Supported Cooperative Work in Design (CSCWD), pp. 907–912 (2012). https://doi.org/10.1109/CSCWD.2012.6221929

  22. Franklin, S., Graesser, A.: Is it an agent, or just a program? A taxonomy for autonomous agents. In: International Workshop on Agent Theories, Architectures, and Languages, pp. 21–35. Springer, Berlin (1996)

    Google Scholar 

  23. Franklin, S., Graesser, A.: Intelligent Agents III. Lecture Notes on Artificial Intelligence, pp. 21–35. Springer, Berlin (1997)

    Google Scholar 

  24. Goodfellow, I.J., Bengio, Y., Courville, A.C.: Deep Learning. Adaptive Computation and Machine Learning. MIT Press, Cambridge (2016). http://www.deeplearningbook.org/

    MATH  Google Scholar 

  25. Grimm, V., Railsback, S.F.: Individual-based modeling and ecology. Princeton University Press, Princeton (2013). https://doi.org/10.1515/9781400850624

  26. Hayes-Roth, F., Waterman, D.A., Lenat, D.B.: Building Expert Systems. Addison-Wesley Longman Publishing, Bostoorth (1983)

    Google Scholar 

  27. Hewitt, C.: Viewing control structures as patterns of passing messages. Artif. Intell. 8(3), 323–364 (1977). https://doi.org/10.1016/0004-3702(77)90033-9

    Article  Google Scholar 

  28. Janssen, M.: Complexity and Ecosystem Management: The Theory and Practice of Multi-Agent Systems. Edward Elgar Publishing, Cheltenham (2002)

    Google Scholar 

  29. Jennings, N., Sycara, K., Wooldridge, M.: A roadmap of agent research and development. Auton. Agents Multi-Agent Syst. 1, 7–38 (1998). https://doi.org/10.1023/A:1010090405266

    Article  Google Scholar 

  30. Jennings, N.R.: On agent-based software engineering. Artif. Intell. 117(2), 277–296 (2000). https://doi.org/10.1016/S0004-3702(99)00107-1

    Article  Google Scholar 

  31. Khalil, W., Dombre, E.: Modeling, Identification and Control of Robots. Butterworth-Heinemann (2004)

    Google Scholar 

  32. Liebowitz, J.: Introduction to Expert Systems. Mitchell Publishing, Los Angeles (1988)

    Google Scholar 

  33. Lin, H.: Architectural Design of Multi-Agent Systems: Technologies and Techniques: Technologies and Techniques. IGI Global, Pennsylvania (2007)

    Google Scholar 

  34. Masters, P., Sardina, S.: Expecting the unexpected: goal recognition for rational and irrational agents. Artif. Intell. 297, 103490 (2021). https://doi.org/10.1016/j.artint.2021.103490

    Article  MathSciNet  Google Scholar 

  35. Mondal, B.: Artificial intelligence: state of the art. Recent Trends Adv. Artif. Intell. Internet Things 389–425 (2020). https://doi.org/10.1007/978-3-030-32644-9_32

  36. Monostori, L., Váncza, J., Kumara, S.R.: Agent-based systems for manufacturing. CIRP Ann. 55(2), 697–720 (2006)

    Article  Google Scholar 

  37. Newman, M.E.J.: Modularity and community structure in networks. Proc. Nat. Acad. Sci. 103(23), 8577–8582 (2006). https://doi.org/10.1073/pnas.0601602103

    Article  Google Scholar 

  38. Poole, D.L., Mackworth, A.K.: Artificial Intelligence: Foundations of Computational Agents. Cambridge University Press, Cambridge (2010). https://doi.org/10.1017/9781108164085

  39. Russell, S.J., Norvig, P.: Artificial Intelligence: A Modern Approach. Prentice Hall Series in Artificial Intelligence. Prentice Hall, Englewood Cliffs (1995). https://www.worldcat.org/oclc/31288015

  40. Sibbel, R., Urban, C.: Agent-based modeling and simulation for hospital management. In: Cooperative Agents, pp. 183–202. Springer, Berlin (2001)

    Google Scholar 

  41. Silva, V., Garcia, A., Brandão, A., Chavez, C., Lucena, C., Alencar, P.: Taming agents and objects in software engineering. In: International Workshop on Software Engineering for Large-Scale Multi-Agent Systems, pp. 1–26. Springer, Berlin (2002). https://doi.org/10.1007/3-540-35828-5_1

  42. Simon, H.A.: Bounded rationality. In: Utility and Probability, pp. 15–18. Springer, Berlin (1990)

    Google Scholar 

  43. Singh, D., Padgham, L., Logan, B.: Integrating BDI agents with agent-based simulation platforms: (JAAMAS extended abstract). In: Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems, AAMAS ’17, pp. 249–250. International Foundation for Autonomous Agents and Multiagent Systems, Richland (2017). http://dl.acm.org/citation.cfm?id=3091125.3091165

  44. Sowa, J.F., Zachman, J.A.: Extending and formalizing the framework for information systems architecture. IBM Syst. J. 31(3), 590–616 (1992). https://doi.org/10.1147/sj.313.0590

    Article  Google Scholar 

  45. Sterling, L., Taveter, K.: The Art of Agent-Oriented Modeling. The MIT Press, Cambridge (2009). https://doi.org/10.7551/mitpress/7682.001.0001

  46. Sulis, E., Humphreys, L., Vernero, F., Amantea, I.A., Audrito, D., Di Caro, L.: Exploiting co-occurrence networks for classification of implicit inter-relationships in legal texts. Inform. Syst. 101821 (2021). https://doi.org/10.1016/j.is.2021.101821

  47. Sun, R., et al.: Cognition and multi-agent interaction: from cognitive modeling to social simulation. Cambridge University Press, Cambridge (2006). https://doi.org/10.1017/CBO9780511610721

  48. Taveter, K., Wagner, G.: A multi-perspective methodology for modelling inter-enterprise business processes. In: Arisawa, H., Kambayashi, Y., Kumar, V., Mayr, H.C., Hunt, I. (eds.) ER 2001 Workshops, HUMACS, DASWIS, ECOMO, and DAMA, Yokohama Japan, November 27–30, 2001, Revised Papers. Lecture Notes in Computer Science, vol. 2465, pp. 403–416. Springer, Berlin (2001). https://doi.org/10.1007/3-540-46140-X_31

    Google Scholar 

  49. van der Aalst, W., Bichler, M., Heinzl, A.: Robotic process automation (2018). https://doi.org/10.1007/s12599-018-0542-4

  50. Watts, D.J., Strogatz, S.H.: Collective dynamics of small-world networks. Nature 393(6684), 440–442 (1998). https://doi.org/10.1038/30918

    Article  Google Scholar 

  51. Weiss, G.: Multiagent Systems. The MIT Press, Cambridge (2013)

    Google Scholar 

  52. Wooldridge, M., Jennings, N.R.: Intelligent agents: theory and practice. Knowl. Eng. Rev. 10(2), 115–152 (1995). https://doi.org/10.1017/S0269888900008122

    Article  Google Scholar 

  53. Wright, J.: International Encyclopedia of the Social & Behavioral Sciences, vol. 11. Elsevier, Amsterdam (2015)

    Google Scholar 

  54. Zachman, J.A.: A framework for information systems architecture. IBM Syst. J. 26(3), 276–292 (1987). https://doi.org/10.1147/sj.263.0276

    Article  Google Scholar 

  55. Zimmer, N.: Socio-technical modeling and simulation of airline operations control. Doctoral Thesis, Technische Universität Braunschweig, Germany (2020)

    Google Scholar 

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Sulis, E., Taveter, K. (2022). Agents and Organization Studies. In: Agent-Based Business Process Simulation. Springer, Cham. https://doi.org/10.1007/978-3-030-98816-6_3

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  • DOI: https://doi.org/10.1007/978-3-030-98816-6_3

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