Etmen-tabanlı modellemede belirme ve karmaşıklık: Güncel araştırmaların incelenmesi

Abstract

Agent-based systems are an important application area of artificial intelligence and are used in decision support systems. Rather than being a problem-solving tool, agent-based system is a tool for developing and testing alternative solutions according to various scenarios. In this context, agent-based modeling is a very effective method to support decision makers in emergency situations to evaluate different risk scenarios and then make decisions quickly and effectively. Moreover, agent-based modeling is a very useful method to support decision makers in situations of high complexity and uncertainty. This paper introduces current studies performed with several agent-based modeling tools and software environments such as NetLogo, AnyLogic, MATSim and Repast. Apart from these, various agent-based modeling tools exist, but these four tools have been chosen because they are still receiving software updates and being widely used in the most current studies. The aims of this study are to review these four agent-based modeling tools, present state-of-the-art research conducted with these tools and provide a reference of agent-based modeling tools for researchers who are developing decision support systems in architectural, urban and transportation design research fields. In this paper, after giving a brief definition of an agent-based system and explaining the importance of concepts such as emergence and complexity in the field of agent-based modeling, it is explained who uses the agentbased models for what purpose, when, where, why and how to use agent-based modeling through selected examples from state-of-the-art studies carried out in different research fields. Furthermore, what current studies and agent-based modeling tools teach us and how future studies can benefit from agent-based models are briefly discussed.

A study of Tennis Tournaments by Means of an Agent-Based Model Calibrated with a Genetic Algorithm

“…In this paper, as in other works cited above, we want to construct an agent-based model [16], a type of model used for the study of complex systems [17,18] in a wide range of scientific fields [19][20][21]; useful for reproducing relations between simulated agents and a virtual environment composed of a set of rules. However, we want to avoid constraining the parameters of the model, in order to obtain information on all the parameters that are important for the competitions, according to the model, and so obtain also information that has been inferred in other works.…”

An agent-based modelling framework for the simulation of large-scale consumer participation in electricity market ecosystems

“…In this study, the methods are provided by predefined roles, the data is provided by the market context, and their combination creates the modelled electricity market ecosystem. The model framework in Vaerbak et al (2021) and in this study are developed in Anylogic, a Java-based software with agentbased modelling features (Cenani 2021). OOP concepts in this section will therefore be referred to using Java programming language.…”