Skip to main content

Agent-Based Simulation Model of Sexual Selection Mechanism

  • Conference paper
  • First Online:
Agent and Multi-Agent Systems: Technologies and Applications

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 38))

  • 1215 Accesses

Abstract

Agent-based approach is especially applicable and useful in modeling and simulation of social and biological systems and mechanisms. In this paper a formal agent-based model of sexual selection mechanism is presented. The paper includes results of simulation experiments aimed at showing whether sexual selection can trigger speciation processes and maintain genetic population diversity. We show that in certain conditions sexual selection mechanism and co-evolution of sexes resulting from it, can lead to formation of new species.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Bäck, T., Fogel, D.B., Whitley, D., Angeline, P.J.: Mutation. In: Bäck, T., Fogel, D., Michalewicz, Z. (eds.) Handbook of Evolutionary Computation. IOP Publishing and Oxford University Press, Oxford (1997)

    Google Scholar 

  2. Booker, L.B., Fogel, D.B., Whitley, D., Angeline, P.J.: Recombination. In: Bäck, T., Fogel, D., Michalewicz, Z. (eds.) Handbook of Evolutionary Computation. IOP Publishing and Oxford University Press, Oxford (1997)

    Google Scholar 

  3. Cetnarowicz, K., Kisiel-Dorohinicki, M., Nawarecki, E.: The application of evolution process in multi-agent world to the prediction system. In: Tokoro, M. (ed.) Proceedings of the 2nd International Conference on Multi-Agent Systems (ICMAS 1996). AAAI Press, Menlo Park (1996)

    Google Scholar 

  4. Dreżewski, R.: A model of co-evolution in multi-agent system. In: Mar̆ík, V., Müller, J., Pĕchouček, M. (eds.) Multi-Agent Systems and Applications III, 3rd International Central and Eastern European Conference on Multi-Agent Systems, CEEMAS 2003, Prague, Czech Republic, June 16–18, 2003, Proceedings. LNCS, vol. 2691, pp. 314–323. Springer, Berlin (2003)

    Google Scholar 

  5. Dreżewski, R.: Co-evolutionary multi-agent system with speciation and resource sharing mechanisms. Comput. Inf. 25(4), 305–331 (2006)

    MATH  Google Scholar 

  6. Dreżewski, R.: Agent-based modeling and simulation of species formation processes. In: Alkhateeb, F., Al Maghayreh, E., Abu Doush, I. (eds.) Multi-Agent Systems – Modeling, Interactions, Simulations and Case Studies, pp. 3–28. InTech, Rijeka (2011)

    Google Scholar 

  7. Dreżewski, R., Sepielak, J.: Evolutionary system for generating investment strategies. In: M. Giacobini, et al. (ed.) Applications of Evolutionary Computing, EvoWorkshops 2008: EvoCOMNET, EvoFIN, EvoHOT, EvoIASP, EvoMUSART, EvoNUM, EvoSTOC, and EvoTransLog, Naples, Italy, 26–28 March 2008. Proceedings. LNCS, vol. 4974, pp. 83–92. Springer, Berlin, Heidelberg (2008)

    Google Scholar 

  8. Dreżewski, R., Siwik, L.: Multi-objective optimization using co-evolutionary multi-agent system with host-parasite mechanism. In: Alexandrov, V.N., van Albada, G.D., Sloot, P.M.A., Dongarra, J. (eds.) Computational Science—ICCS 2006, 6th International Conference, Reading, UK, May 28–31, 2006, Proceedings, Part III. LNCS, vol. 3993, pp. 871–878. Springer, Berlin (2006)

    Google Scholar 

  9. Dreżewski, R., Siwik, L.: Multi-objective optimization technique based on co-evolutionary interactions in multi-agent system. In: Giacobini, M., et al. (eds.) Applications of Evolutinary Computing, EvoWorkshops 2007: EvoCoMnet, EvoFIN, EvoIASP, EvoINTERACTION, EvoMUSART, EvoSTOC and EvoTransLog, Valencia, Spain, April11-13, 2007, Proceedings. LNCS, vol. 4448, pp. 179–188. Springer, Berlin (2007)

    Chapter  Google Scholar 

  10. Dreżewski, R., Siwik, L.: Agent-based co-operative co-evolutionary algorithm for multi-objective optimization. In: Rutkowski, L., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) Artificial Intelligence and Soft Computing—ICAISC 2008, 9th International Conference, Zakopane, Poland, June 22–26, 2008, Proceedings. LNCS, vol. 5097, pp. 388–397. Springer, Berlin (2008)

    Google Scholar 

  11. Epstein, J.M.: Generative Social Science. Studies in Agent-Based Computational Modeling. Princeton University Press, Princeton (2006)

    MATH  Google Scholar 

  12. Epstein, J.M., Axtell, R.: Growing Artificial Societes. Social Science from Bottom Up. Brookings Institution Press, The MIT Press, Washington, DC (1996)

    Google Scholar 

  13. Ferber, J.: Multi-Agent Systems: An Introduction to Distributed Artificial Intelligence. Addison-Wesley, Boston (1999)

    Google Scholar 

  14. Gavrilets, S.: Models of speciation: what have we learned in 40 years? Evolution 57(10), 2197–2215 (2003)

    Article  Google Scholar 

  15. Gilbert, N.: Agent-based models. SAGE Publications, London (2008)

    Google Scholar 

  16. Gilbert, N., Troitzsch, K.G.: Simulation for the social scientist. Open University Press, Buckingham (2005)

    Google Scholar 

  17. Krebs, J., Davies, N.: An Introduction to Behavioural Ecology. Blackwell Science Ltd, Oxford (1993)

    Google Scholar 

  18. Potter, M.A.: The design and analysis of a computational model of cooperative coevolution. Ph.D. thesis, George Mason University, Fairfax, Virginia (1997)

    Google Scholar 

  19. Uhrmacher, A.M., Weyns, D. (eds.): Multi-agent Systems. Simulation and Applications. CRC Press, Boca Raton (2009)

    Google Scholar 

  20. Ursem, R.K.: Multinational evolutionary algorithms. In: Angeline, P.J., Michalewicz, Z., Schoenauer, M., Yao, X., Zalzala, A. (eds.) Proceedings of the 1999 Congress on Evolutionary Computation (CEC-1999), pp. 1633–1640. IEEE Press, Piscataway (1999)

    Google Scholar 

Download references

Acknowledgments

This research was partially supported by Polish Ministry of Science and Higher Education under AGH University of Science and Technology Grant (statutory project).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Rafał Dreżewski .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this paper

Cite this paper

Dreżewski, R. (2015). Agent-Based Simulation Model of Sexual Selection Mechanism. In: Jezic, G., Howlett, R., Jain, L. (eds) Agent and Multi-Agent Systems: Technologies and Applications. Smart Innovation, Systems and Technologies, vol 38. Springer, Cham. https://doi.org/10.1007/978-3-319-19728-9_13

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-19728-9_13

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19727-2

  • Online ISBN: 978-3-319-19728-9

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics