Agent-Based Computational Modelling: An Introduction

Billari, Francesco C.; Fent, Thomas; Prskawetz, Alexia; Scheffran, Jürgen

doi:10.1007/3-7908-1721-x_1

Cited by 46 publications

(44 citation statements)

References 23 publications

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“…So far the bulk of modern agent-based models have been deployed in epidemiology and population health (Auchincloss and Diez-Roux, 2008) but there are clear indications that their use is spreading and catching on elsewhere in sociology and demography (Centola, 2010;Macy and Willer, 2002;Billari et al, 2006;Axelrod, 1997a,b). While none of the applications to date are explicitly designed to deal with diffusion processes, the extension is not complicated and one could easily imagine how diffusion models that include the complexity implied by social interactions and network models could lead to standard agent-based models.…”

Section: Agent-based Modelsmentioning

confidence: 97%

Diffusion in Sociological Analysis

Palloni

2015

International Encyclopedia of the Social &Amp; Behavioral Sciences

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Section: Agent-based Modelsmentioning

confidence: 97%

Diffusion in Sociological Analysis

Palloni

2015

International Encyclopedia of the Social &Amp; Behavioral Sciences

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“…ABM is a computationally intensive dynamic simulation Downloaded by [New York University] at 13:54 23 June 2015 model of how individual agents (typically using simple behavioural rules) interact with their environment and each other, giving rise to system-wide macro patterns or emergent properties which cannot be deduced from the individual agent's rules (Billari et al, 2006;Tefatsion, 2006;Garifullin et al, 2007). Agents can be individual persons (e.g.…”

Section: What Is Agent-based Modelling (Abm)?mentioning

confidence: 99%

“…Agents use these endowments to observe their aggregate environment (including other agents), form expectations, and provide updates to their preferences (learning). The rules, search routines, and potential actions or decisions of each agent are specified, and the system is simulated in a 'cycle of action, evaluation, and updat[ing]' (Billari et al, 2006). While the model is defined solely at the micro (agent) scale, agent interactions produce distributions of outcomes that may have macro-level regularities, equilibria, and the dynamics of the system as a whole (Billari et al, 2006).…”

Section: What Is Agent-based Modelling (Abm)?mentioning

confidence: 99%

The Potential of Agent-Based Modelling for Performing Economic Analysis of Adaptive Natural Resource Management

Loomis

Bond

Harpman

2009

Journal of Natural Resources Policy Research

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This paper explores how individual agent-based modelling can be used by economists and others to evaluate the economic aspects of adaptive management of natural resources. To date, economists have had few tools to perform economic analysis on adaptive natural resource management strategies and there has been limited economic analysis of adaptive management. Part of the reason for this situation may be the inherent nature of adaptive management which involves a series of ‘if-then’ in situ experiments in which expected outputs are not known with certainty, and future management actions depend on the outcome of the experiments. Individual agent-based modelling allows simulation of system wide emergent ecosystem properties that can reflect adaptation of individual agents with bounded rationality to their environment and to the interaction with other agents. These simulations can be used to mimic adaptive management experiments when insufficient information is available for more structured equation-based simulation models. The distribution of simulated outputs from individual agent-based models along with costs of the management actions may give economists the ability to better apply economic analysis to evaluate alternative adaptive management strategies.

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“…There has never been a generalization of the agent based model. Variety of models have been proposed in demographic context [24], some example are: family formation: Todd, Billari & Simao [17]; Billari [18]; Billari et al [19], [20]; Hills and Todd [21]; Aparicio-Diaz et al [22]; E. Frydenlund [23] [28], Household Dynamics: Geard et al [29]. As we can see that these models are specific in nature and the high-level framework which brings together various aspects of the agent based simulation is missing.…”

Section: B Agent Based Demographic Modelsmentioning

confidence: 99%

Simulating Population Dynamics with an Agent Based and Microsimulation Based Framework

Singh¹,

Sajjad²,

Ahn³

2016

Proceedings of the 3d International Conference on Applied Social Science Research

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-Simulation has been an important way of modeling and for predicting and analyzing population dynamics related phenomena. There have been many advances in this field and various techniques have been applied for prediction and understanding. Microsimulation and multi agent based simulation are two of the most suitable techniques which give us results that could be related to the real world phenomena. Applying these techniques enable us to perform various multi-dimensional policy experiments on demography related processes. Of these two techniques, microsimulation has been around for longer time, but of late, agent based techniques have become very popular. These models are being used more and more in the social sciences. Both of techniques have similarities and as well as differences. We will explore these techniques and propose a new framework which has positive aspects of both the approaches.

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Agent-Based Computational Modelling: An Introduction

Cited by 46 publications

References 23 publications

Diffusion in Sociological Analysis

Diffusion in Sociological Analysis

The Potential of Agent-Based Modelling for Performing Economic Analysis of Adaptive Natural Resource Management

Simulating Population Dynamics with an Agent Based and Microsimulation Based Framework

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