Research Article
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ESTIMATION OF THE AGENT BEHAVIORS BY USING THE TAYLOR SERIES APPROXIMATION

Year 2020, , 35 - 44, 29.12.2020
https://doi.org/10.21923/jesd.828792

Abstract

In the agent-based modeling approach, agents play an important role in determining the behavior of the system. The agents are autonomous components of the agent-based model of a real system. An agent is defined as having a set of features and rules governing behavior and decision-making. In this study, a numerical solution is presented for determining some rules of behaviors of agents. Behavioral functions that will guide the actions of the agents in the model are handled with the Taylor series approach. The Taylor series can estimate a function value at the initial agent in terms of the function value and its derivatives at another agent. An agent-based cross-sectional model is examined with some experimental results by using Taylor series expansion. Compared to the results of the study which is presented with the agent-based modeling approach, the Taylor Series obtains successful solutions based on distance points of the agents. This study presents a hybrid model perspective by proposing a numerical method approach to determining agent behaviors.

References

  • Bonabeau, E., 2002. Agent-based modeling: Methods and techniques for simulating human systems, Proceedings of the National Academy of Sciences, 99(3):7280–7287 pp.
  • Bora, Ş., Evren, V., Emek, S. and Çakırlar, I., 2017. Agent-based modeling and simulation of blood vessels in the cardiovascular system. Simulation: Transactions of the Society for Modeling and Simulation International, Special Section on Medical M&S in Simulation. DOI: 10.1177/0037549717712602
  • Chapra S., C., Canale, R., P., 2015. Numerical Methods for Engineers, 7th Ed., Published by McGraw-Hill Education.
  • Di Marzo Serugendo, G., Gleizes, M.-P. and Karageorgos, A., 2005. Self-organization in multi-agent systems, The Knowledge Engineering Review, 20(2):165–189 pp. doi: 10.1017/S0269888905000494
  • Emek, S., 2018. Modeling and Simulation of Global Behaviors of the Self-Adaptive Systems by Using Agent Based System, PhD, Ege University, Izmir, Turkey.
  • Li, J. K-J., 2004. Dynamics of the vascular system. World Scientific Publishing, 1: 257p.
  • Macal, C. M. and North, M. J., 2009. Agent-Based Modeling and Simulation. In: WSC’09 Winter Simulation Conference, 86-98 pp.
  • Macal, C. M. and North, M. J., 2010. Tutorial on agent-based modeling and simulation. Journal of simulation, 4(3):151-162 pp.
  • Mangai, S., A., Sankar, B., R., Alagarsamy, K., 2014. Taylor Series Prediction of Time Series Data with Error Propagated by Artificial Neural Network, International Journal of Computer Applications, Vol. 89, No. 1.

TAYLOR SERİSİ İLE ETMEN DAVRANIŞLARININ TAHMİNLENMESİ

Year 2020, , 35 - 44, 29.12.2020
https://doi.org/10.21923/jesd.828792

Abstract

Etmen tabanlı modelleme yaklaşımında, modellenen sistemin davranışının belirlenmesinde etmenler önemli rol oynamaktadır. Etmenler gerçek bir sistem modelinin otonom bileşenleridir. Bir etmen, davranışlarını ve karar verme yeteneğini yöneten bir dizi özellik ve kurala sahip olarak tanımlanmaktadır. Bu çalışmada, etmenlerin bazı davranış kurallarının belirlenmesinde nümerik bir çözüm sunulmaktadır. Model içinde etmenlerin eylemlerini gerçekleştirmesine yön verecek davranış fonksiyonları Taylor serisi yaklaşımı ile ele alınmaktadır. Taylor serisi, başlangıç etmenindeki bir fonksiyon değerini, fonksiyon değeri ve başka bir ajandaki türevleri açısından tahmin edebilmektedir. Etmen tabanlı kesitsel bir model, Taylor serisi açılımı kullanılarak bazı deneysel sonuçlarla incelenmektedir. Etmen tabanlı modelleme yaklaşımı ile sunulan çalışmanın sonuçları karşılaştırıldığında Taylor Serisi, etmenlerin uzaklık noktalarına göre başarılı çözümler elde etmektedir. Bu çalışma, etmen davranışlarına nümerik bir metot yaklaşımı önermesi ile hibrid bir model perspektifi sunmaktadır.

References

  • Bonabeau, E., 2002. Agent-based modeling: Methods and techniques for simulating human systems, Proceedings of the National Academy of Sciences, 99(3):7280–7287 pp.
  • Bora, Ş., Evren, V., Emek, S. and Çakırlar, I., 2017. Agent-based modeling and simulation of blood vessels in the cardiovascular system. Simulation: Transactions of the Society for Modeling and Simulation International, Special Section on Medical M&S in Simulation. DOI: 10.1177/0037549717712602
  • Chapra S., C., Canale, R., P., 2015. Numerical Methods for Engineers, 7th Ed., Published by McGraw-Hill Education.
  • Di Marzo Serugendo, G., Gleizes, M.-P. and Karageorgos, A., 2005. Self-organization in multi-agent systems, The Knowledge Engineering Review, 20(2):165–189 pp. doi: 10.1017/S0269888905000494
  • Emek, S., 2018. Modeling and Simulation of Global Behaviors of the Self-Adaptive Systems by Using Agent Based System, PhD, Ege University, Izmir, Turkey.
  • Li, J. K-J., 2004. Dynamics of the vascular system. World Scientific Publishing, 1: 257p.
  • Macal, C. M. and North, M. J., 2009. Agent-Based Modeling and Simulation. In: WSC’09 Winter Simulation Conference, 86-98 pp.
  • Macal, C. M. and North, M. J., 2010. Tutorial on agent-based modeling and simulation. Journal of simulation, 4(3):151-162 pp.
  • Mangai, S., A., Sankar, B., R., Alagarsamy, K., 2014. Taylor Series Prediction of Time Series Data with Error Propagated by Artificial Neural Network, International Journal of Computer Applications, Vol. 89, No. 1.
There are 9 citations in total.

Details

Primary Language English
Subjects Computer Software, Engineering
Journal Section Research Articles
Authors

Sevcan Emek 0000-0003-2207-8418

Şebnem Bora 0000-0003-0111-4635

Publication Date December 29, 2020
Submission Date November 20, 2020
Acceptance Date December 22, 2020
Published in Issue Year 2020

Cite

APA Emek, S., & Bora, Ş. (2020). TAYLOR SERİSİ İLE ETMEN DAVRANIŞLARININ TAHMİNLENMESİ. Mühendislik Bilimleri Ve Tasarım Dergisi, 8(5), 35-44. https://doi.org/10.21923/jesd.828792