Interconnected Conditions of Homogeneous and Heterogeneous Behavior in Agent-Based Models: Matrix with Calculated Vectors

Chulwook Park

doi:10.26717/bjstr.2020.25.004233

Abstract

Chulwook Park*1,2 Author Affiliations 1Department of Evolution and Ecology (International Institute for Applied Systems Analysis), Austria 2Department of Physical Science (Seoul National University Institute of Sport Science), Korea Received: November 25, 2020 | Published: February 18, 2020 Corresponding author: Chulwook Park, International Institute for Applied Systems Analysis, A-2361 Laxenburg, Austria, Department of Physical Science, Seoul National University Institute of Sport Science, 08826 Seoul, Korea DOI: 10.26717/BJSTR.2020.25.004233

Highlights

The broader agenda of this model is to especially understand the conditions leading to the estimation of behavioral bias [1] by including a fundamental modeling perspective with the cultural evolutionary process [2]
Their external properties come from network characteristics representing social ties, and mutations are related to how quickly the risk function propagates throughout the network
The movement is affected by the trade-off between the direction of the individual velocity-group and and their actions, including their network properties, based on social ties multiplied by the rate of of individual movements and their network characteristics as mutations

Summary

Introduction

The broader agenda of this model is to especially understand the conditions leading to the estimation of behavioral bias [1] by including a fundamental modeling perspective with the cultural evolutionary process [2]. Bias (or systemic risk) is a property of systems of interconnected components, and can be defined as “system instability, potentially catastrophic, caused or exacerbated by idiosyncratic events” [3]. Investigations have been risk for various high-profile disasters, describing it as posing the likelihood of cascading failures [4] because of the complex interactions that can take place among individual system elements or through their association [5]. The context-varying mechanical flux on the system’s bias is, very complex [6]. In view of all these possible distortions and patterns of influences, the possibility of quantifying bias within a system and capturing its size needs to be established. Where an event in a particular form could trigger instability or collapse an entire system, regardless of the capability of the individual system elements at that point, it is possible to quantify with specificity the mechanisms underlying the computerized model implementation

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