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What is Agent-Based Modeling

Chapter 17
Handbook of Research on Nature-Inspired Computing for Economics and Management
Modeling refers to the process of designing a software representation of a real-world system or a small part of it with the purpose of replicating or simulating specific features of the modeled system. In an agent-based model, the model behavior results from behavior of many small software entities called agents. This technique is used to model real-world systems comprised of many decision-making entities with inhomogeneous preferences, knowledge, and decision-making processes. An advantage of this method is that no assumptions need to be made about an aggregate or mean behavior. Instead, this aggregation is made by the model. See Davidsson (2002) for a topology of different modeling techniques including what he calls agent-based social simulation, and see Tesfatsion (2002) for a discussion of agent-based computational economics. Hare and Deadman (2004) discuss different uses of agent-based models in environmental management.
Published in Chapter:
Agent-Based Modelnig with Boundedly Rational Agents
E. Ebenhoh (University of Osnabrück, Germany)
Copyright: © 2007 |Pages: 21
DOI: 10.4018/978-1-59140-984-7.ch017
Abstract
This chapter introduces an agent-based modeling framework for reproducing micro behavior in economic experiments. It gives an overview of the theoretical concept which forms the foundation of the framework as well as short descriptions of two exemplary models based on experimental data. The heterogeneous agents are endowed with a number of attributes like cooperativeness and employ more or less complex heuristics during their decision-making processes. The attributes help to distinguish between agents, and the heuristics distinguish between behavioral classes. Through this design, agents can be modeled to behave like real humans and their decision making is observable and traceable, features that are important when agent-based models are to be used in collaborative planning or participatory model-building processes.
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Chapter 3
Agent-Based Modeling: A Historical Perspective and a Review of Validation and Verification Efforts
A computational model for simulating the actions and interactions of autonomous individuals in a network, with a view to assessing their effects on the system as a whole.
Published in Chapter: Agent-Based Modeling: A Historical Perspective and a Review of Validation and Verification Efforts; From: Handbook of Research on Discrete Event Simulation Environments: Technologies and Applications
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Chapter 25
Multi-Agent Systems for Distributed Geospatial Modeling, Simulation and Computing
In artificial life, it is the set of techniques in which relations and descriptions of global variables are represented with an explicit representation of microscopic features of the system, typically in the form of agents that interact with each other and their environment according to rules in a discrete space-time.
Published in Chapter: Multi-Agent Systems for Distributed Geospatial Modeling, Simulation and Computing; From: Handbook of Research on Geoinformatics
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Chapter 43
Worker Performance Modeling in Manufacturing Systems Simulation
In the context of this chapter, this is a bottom-up approach that allows the behavior of human beings to be captured in a more realistic fashion. The artificial agents acting as representatives for real factory workers have to be designed to mimic the attributes and behaviors of their real-world counterparts as similarly as possible. The system’s macro-observable properties emerge as a consequence of these attributes and behaviors, and the interactions between them.
Published in Chapter: Worker Performance Modeling in Manufacturing Systems Simulation; From: Handbook of Research on Nature-Inspired Computing for Economics and Management
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