Agent-based modeling and simulation: ABMS examples

Abstract

Agent-based modeling and simulation (ABMS) is a new approach to modeling systems comprised of autonomous, interacting agents. ABMS promises to have far-reaching effects on the way that businesses use computers to support decision-making and researchers use electronic laboratories to support their research. Some have gone so far as to contend that ABMS "is a third way of doing science," in addition to traditional deductive and inductive reasoning (Axelrod 1997). Computational advances have made possible a growing number of agent-based models across a variety of application domains. Applications range from modeling agent behavior in the stock market, supply chains, and consumer markets, to predicting the spread of epidemics, the threat of bio-warfare, and the factors responsible for the fall of ancient civilizations. This tutorial describes the theoretical and practical foundations of ABMS, identifies toolkits and methods for developing agent models, and illustrates the development of a simple agent-based model.

Economic Evaluations with Agent-Based Modelling: An Introduction

“…Modelling tool selection should depend on the complexity of the problem, the quantitative training of the modeller, and the time available to complete the project. More details on ABM software and toolkits can be found elsewhere [9,47].…”

“…These include introductory-level books [49], software-specific books for NetLogo [10] and Swarm [50], and books in the fields of social science [51,52] and business management [53]. In addition, several tutorials have been published in different fields that can be useful in learning the scope of ABM [9,[54][55][56].…”

“…ABMs have been applied successfully to a wide range of topics, such as traffic management, customer flow management, prediction of stock markets, analysis of operational risk, the military, biological sciences and infectious disease control [8,9]. The need for ABM is expected to increase as decision-making becomes more complex and as data availability increases.…”

Identifying and Quantifying Emergent Behavior Through System of Systems Modeling and Simulation

“…Still others felt that emergence is part of the "coherent structures, patterns and properties that arise during the self-organization in complex systems." Macal and North (2008) states that when the behavior of an agent affects other agents, and those agents' behaviors ultimately affect the original agent, a complex feedback dynamic is put in motion that produces emergence. Li, Sim, and Low (2006) states that software agents cannot act like people due to speed of their decisions, lack of flexibility, and learning difficulties.…”

Towards a standard model for research in agent-based modeling and simulation

“…The global behavior of the system is the result from the simple, self-organized local relationships between the agents (Fachada, 2008). As such, ABM is a useful tool in simulating and exploring systems that can be modeled in terms of interactions between individual entities, e.g., biological cell cultures, ants foraging for food or military units in a battlefield (Macal & North, 2008). In practice, ABM can be considered a variation of discrete-event simulation, since state changes occur at specific points in time (Law, 2015).…”