IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v9y2021i1p103-d475057.html
   My bibliography  Save this article

Intelligent Agents in Co-Evolving Knowledge Networks

Author

Listed:
  • Evangelos Ioannidis

    (Complex Systems Analysis Laboratory (COSAL), Faculty of Sciences, School of Mathematics, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece)

  • Nikos Varsakelis

    (Complex Systems Analysis Laboratory (COSAL), Faculty of Economic and Political Sciences, School of Economics, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece)

  • Ioannis Antoniou

    (Complex Systems Analysis Laboratory (COSAL), Faculty of Sciences, School of Mathematics, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece)

Abstract

We extend the agent-based models for knowledge diffusion in networks, restricted to random mindless interactions and to “frozen” (static) networks , in order to take into account intelligent agents and network co-evolution . Intelligent agents make decisions under bounded rationality. This is the key distinction of intelligent interacting agents compared to mindless colliding molecules , involved in the usual diffusion mechanism resulting from accidental collisions. The co-evolution of link weights and knowledge levels is modeled at the local microscopic level of “agent-to-agent” interaction . Our network co-evolution model is actually a “ learning mechanism” , where weight updates depend on the previous values of both weights and knowledge levels. The goal of our work is to explore the impact of (a) the intelligence of the agents, modeled by the selection-decision rule for knowledge acquisition, (b) the innovation rate of the agents, (c) the number of “top innovators” and (d) the network size . We find that rational intelligent agents transform the network into a “centralized world” , reducing the entropy of their selections-decisions for knowledge acquisition. In addition, we find that the average knowledge , as well as the “knowledge inequality” , grow exponentially.

Suggested Citation

  • Evangelos Ioannidis & Nikos Varsakelis & Ioannis Antoniou, 2021. "Intelligent Agents in Co-Evolving Knowledge Networks," Mathematics, MDPI, vol. 9(1), pages 1-17, January.
  • Handle: RePEc:gam:jmathe:v:9:y:2021:i:1:p:103-:d:475057
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/9/1/103/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/9/1/103/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ioannidis, Evangelos & Varsakelis, Nikos & Antoniou, Ioannis, 2018. "Communication Policies in Knowledge Networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 360-374.
    2. Ioannidis, Evangelos & Varsakelis, Nikos & Antoniou, Ioannis, 2019. "Change agents and internal communications in organizational networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 528(C).
    3. Fan, Kangqi & Pedrycz, Witold, 2016. "Opinion evolution influenced by informed agents," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 431-441.
    4. Cowan, Robin & Jonard, Nicolas, 2004. "Network structure and the diffusion of knowledge," Journal of Economic Dynamics and Control, Elsevier, vol. 28(8), pages 1557-1575, June.
    5. Zhu, Hong-Miao & Zhang, Sheng-Tai & Jin, Zhen, 2016. "The effects of online social networks on tacit knowledge transmission," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 441(C), pages 192-198.
    6. Ioannidis, Evangelos & Varsakelis, Nikos & Antoniou, Ioannis, 2018. "Experts in Knowledge Networks: Central Positioning and Intelligent Selections," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 890-905.
    7. Pan, Raj K. & Petersen, Alexander M. & Pammolli, Fabio & Fortunato, Santo, 2018. "The memory of science: Inflation, myopia, and the knowledge network," Journal of Informetrics, Elsevier, vol. 12(3), pages 656-678.
    8. Morten T. Hansen, 2002. "Knowledge Networks: Explaining Effective Knowledge Sharing in Multiunit Companies," Organization Science, INFORMS, vol. 13(3), pages 232-248, June.
    9. Cowan, R. & Jonard, N., 2003. "The dynamics of collective invention," Journal of Economic Behavior & Organization, Elsevier, vol. 52(4), pages 513-532, December.
    10. Piergiuseppe Morone & Richard Taylor, 2004. "Knowledge diffusion dynamics and network properties of face-to-face interactions," Journal of Evolutionary Economics, Springer, vol. 14(3), pages 327-351, July.
    11. Cowan, Robin & Jonard, Nicolas & Özman, Müge, 2003. "Knowledge Dynamics in a Network Industry," Research Memorandum 003, Maastricht University, Maastricht Economic Research Institute on Innovation and Technology (MERIT).
    12. Ioannidis, Evangelos & Varsakelis, Nikos & Antoniou, Ioannis, 2017. "False Beliefs in Unreliable Knowledge Networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 470(C), pages 275-295.
    13. Herbert A. Simon, 1955. "A Behavioral Model of Rational Choice," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 69(1), pages 99-118.
    14. Alan Kirman, 1997. "The economy as an evolving network," Journal of Evolutionary Economics, Springer, vol. 7(4), pages 339-353.
    15. Simon, Herbert A, 1979. "Rational Decision Making in Business Organizations," American Economic Review, American Economic Association, vol. 69(4), pages 493-513, September.
    16. Jian-Guo Liu & Guang-Yong Yang & Zhao-Long Hu, 2014. "A Knowledge Generation Model via the Hypernetwork," PLOS ONE, Public Library of Science, vol. 9(3), pages 1-8, March.
    17. Lin, Min & Li, Nan, 2010. "Scale-free network provides an optimal pattern for knowledge transfer," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(3), pages 473-480.
    18. Zhuang, Enyu & Chen, Guanrong & Feng, Gang, 2011. "A network model of knowledge accumulation through diffusion and upgrade," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(13), pages 2582-2592.
    19. Wang, Jiang-Pan & Guo, Qiang & Yang, Guang-Yong & Liu, Jian-Guo, 2015. "Improved knowledge diffusion model based on the collaboration hypernetwork," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 428(C), pages 250-256.
    20. Cremonini, Marco, 2016. "Introducing serendipity in a social network model of knowledge diffusion," Chaos, Solitons & Fractals, Elsevier, vol. 90(C), pages 64-71.
    21. Yang, Guang-Yong & Hu, Zhao-Long & Liu, Jian-Guo, 2015. "Knowledge diffusion in the collaboration hypernetwork," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 429-436.
    22. Lin, Min & Wei, Jun, 2018. "The impact of innovation intermediary on knowledge transfer," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 21-28.
    23. Zhao, Liming & Zhang, Haihong & Wu, Wenqing, 2017. "Knowledge service decision making in business incubators based on the supernetwork model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 479(C), pages 249-264.
    24. Zhang, Haihong & Wu, Wenqing & Zhao, Liming, 2016. "A study of knowledge supernetworks and network robustness in different business incubators," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 447(C), pages 545-560.
    25. Tur, Elena M. & Azagra-Caro, Joaquín M., 2018. "The coevolution of endogenous knowledge networks and knowledge creation," Journal of Economic Behavior & Organization, Elsevier, vol. 145(C), pages 424-434.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ioannidis, Evangelos & Varsakelis, Nikos & Antoniou, Ioannis, 2018. "Experts in Knowledge Networks: Central Positioning and Intelligent Selections," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 890-905.
    2. Ioannidis, Evangelos & Varsakelis, Nikos & Antoniou, Ioannis, 2017. "False Beliefs in Unreliable Knowledge Networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 470(C), pages 275-295.
    3. Liming Zhao & Haihong Zhang & Wenqing Wu, 2019. "Cooperative knowledge creation in an uncertain network environment based on a dynamic knowledge supernetwork," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(2), pages 657-685, May.
    4. Zhao, Liming & Zhang, Haihong & Wu, Wenqing, 2017. "Knowledge service decision making in business incubators based on the supernetwork model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 479(C), pages 249-264.
    5. Yue, Zenghui & Xu, Haiyun & Yuan, Guoting & Pang, Hongshen, 2019. "Modeling study of knowledge diffusion in scientific collaboration networks based on differential dynamics: A case study in graphene field," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 524(C), pages 375-391.
    6. Evangelos Ioannidis & Nikos Varsakelis & Ioannis Antoniou, 2020. "Promoters versus Adversaries of Change: Agent-Based Modeling of Organizational Conflict in Co-Evolving Networks," Mathematics, MDPI, vol. 8(12), pages 1-25, December.
    7. Liao, Shi-Gen & Yi, Shu-Ping, 2021. "Modeling and analysis knowledge transmission process in complex networks by considering internalization mechanism," Chaos, Solitons & Fractals, Elsevier, vol. 143(C).
    8. Wang, Jiang-Pan & Guo, Qiang & Yang, Guang-Yong & Liu, Jian-Guo, 2015. "Improved knowledge diffusion model based on the collaboration hypernetwork," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 428(C), pages 250-256.
    9. Zhang, Haihong & Wu, Wenqing & Zhao, Liming, 2016. "A study of knowledge supernetworks and network robustness in different business incubators," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 447(C), pages 545-560.
    10. Bogner, Kristina, 2019. "Knowledge networks in the German bioeconomy: Network structure of publicly funded R&D networks," Hohenheim Discussion Papers in Business, Economics and Social Sciences 03-2019, University of Hohenheim, Faculty of Business, Economics and Social Sciences.
    11. Lorenzo Cassi & Lorenzo Zirulia, 2008. "The opportunity cost of social relations: On the effectiveness of small worlds," Journal of Evolutionary Economics, Springer, vol. 18(1), pages 77-101, February.
    12. Karolina Safarzyńska & Jeroen Bergh, 2010. "Evolutionary models in economics: a survey of methods and building blocks," Journal of Evolutionary Economics, Springer, vol. 20(3), pages 329-373, June.
    13. Yang, Guang-Yong & Hu, Zhao-Long & Liu, Jian-Guo, 2015. "Knowledge diffusion in the collaboration hypernetwork," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 429-436.
    14. Liao, Shi-Gen & Yi, Shu-Ping, 2021. "Modeling and analyzing knowledge transmission process considering free-riding behavior of knowledge acquisition: A waterborne disease approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 569(C).
    15. Wang, Haiying & Wang, Jun & Ding, Liting & Wei, Wei, 2017. "Knowledge transmission model with consideration of self-learning mechanism in complex networks," Applied Mathematics and Computation, Elsevier, vol. 304(C), pages 83-92.
    16. Cantner, Uwe & Graf, Holger, 2006. "The network of innovators in Jena: An application of social network analysis," Research Policy, Elsevier, vol. 35(4), pages 463-480, May.
    17. Yu Wei & Sun Ning, 2018. "Establishment and Analysis of the Supernetwork Model for Nanjing Metro Transportation System," Complexity, Hindawi, vol. 2018, pages 1-11, December.
    18. Lorenzo Cassi & Lorenzo Zirulia, 2012. "Friends and Rivals: Modelling the Social Relations of Inventors," Working Paper series 39_12, Rimini Centre for Economic Analysis.
    19. Uwe Cantner & Holger Graf, 2011. "Innovation Networks: Formation, Performance and Dynamics," Chapters, in: Cristiano Antonelli (ed.), Handbook on the Economic Complexity of Technological Change, chapter 15, Edward Elgar Publishing.
    20. Xiao Liao & Guangyu Ye & Juan Yu & Yunjiang Xi, 2021. "Identifying lead users in online user innovation communities based on supernetwork," Annals of Operations Research, Springer, vol. 300(2), pages 515-543, May.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:9:y:2021:i:1:p:103-:d:475057. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.