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(11 articles matched your search)

Responsiveness of Mining Community Acceptance Model to Key Parameter Changes
By: Mark Kofi Boateng, Kwame Awuah-Offei, Volume 20 (3)
Abstract: The mining industry has difficulties predicting changes in the level of community acceptance of its projects over time. These changes are due to changes in the society and individual perceptions around these mines as a result of the mines’ environmental and social impacts. Agent-based modeling can be used to facilitate better understanding of how community acceptance changes with changing mine environmental impacts. This work investigates the sensitivity of an agent-based model (ABM) for predicting changes in community acceptance of a mining project due to information diffusion to key input ...

Which Perspective of Institutional Change Best Fits Empirical Data? An Agent-Based Model Comparison of Rational Choice and Cultural Diffusion in Invasive Plant Management
By: Abigail Sullivan, Li An, Abigail York, Volume 21 (1)
Abstract: There are multiple theories regarding how institutions change over time, but institutional change is often difficult to study and understand in practice. Agent-based modeling is known as a technique to explore emergent phenomena resulting from the micro level activities and interactions between heterogeneous agents and between agents and the environment. Such models allow researchers to investigate theories which may otherwise be difficult to examine. We present a theoretically driven agent-based model to explore two perspectives on institutional change, rational choice and cultural diffusion, ...

Integrating Global Sensitivity Approaches to Deconstruct Spatial and Temporal Sensitivities of Complex Spatial Agent-Based Models
By: Nicholas Magliocca, Virginia McConnell, Margaret Walls, Volume 21 (1)
Abstract: Spatial agent-based models (ABMs) can be powerful tools for understanding individual level decision-making. However, in an attempt to represent realistic decision-making processes, spatial ABMs often become extremely complex, making it difficult to identify and quantify sources of model sensitivity. This paper implements a coastal version of the economic agent-based urban growth model, CHALMS, to investigate both space- and time-varying sensitivities of simulated coastal development dynamics. We review the current state of spatially- and temporally-explicit global sensitivity analyses (GSA) fo ...

Automated Analysis of Regularities Between Model Parameters and Output Using Support Vector Regression in Conjunction with Decision Trees
By: Mert Edali, Gönenç Yücel, Volume 21 (4)
Abstract: Opening the black-box of nonlinear relationships between model inputs and outputs, significantly contributes to the understanding of the dynamic problem being studied. Considering the weaknesses and disadvantages of human-guided and systematic techniques offered in the literature, this paper presents a model analysis and exploration tool for agent-based models. The tool first approximates input-output relationships by developing a metamodel, a simplified representation of the original agent-based model. For this purpose, it utilizes support vector regression, which is capable of approximating ...

Explaining the Emerging Influence of Culture, from Individual Influences to Collective Phenomena
By: Loïs Vanhée, Frank Dignum, Volume 21 (4)
Abstract: This paper presents a simulation model and derived from it a theory to explain how known cultural influences on individual decisions lead to collective phenomena. This simulation models the evolution of a business organization, replicating key micro-level cultural influences on individual decisions (such as allocating and accepting tasks) and subsequent macro-level collective cultural phenomena (such as robustness and sensitivity to environmental complexity). As a result, we derived a theory on how to relate the influence of culture from individual decisions to collective outcomes, based on th ...

The Evolution of Tribalism: A Social-Ecological Model of Cooperation and Inter-Group Conflict Under Pastoralism
By: Nicholas Seltzer, Volume 22 (2)
Abstract: This study investigates a possible nexus between inter-group competition and intra-group cooperation, which may be called "tribalism." Building upon previous studies demonstrating a relationship between the environment and social relations, the present research incorporates a social-ecological model as a mediating factor connecting both individuals and communities to the environment. Cyclical and non-cyclical fluctuation in a simple, two-resource ecology drive agents to adopt either "go-it-alone" or group-based survival strategies via evolutionary selection. Novelly, this s ...

An Agent-Based Model of Firm Size Distribution and Collaborative Innovation
By: Inyoung Hwang, Volume 23 (1)
Abstract: ICT-based Collaborative innovation has a significant impact on the economy by facilitating technological convergence and promoting innovation in other industries. However, research on innovation suggests that polarization in firm size distribution, which has grown since the early 2000s, can interfere with collaborative innovation among firms. In this paper, I modelled firms’ decision-making processes that led to collaborative innovation as a spatial N-person iterated Prisoner’s dilemma (NIPD) game using collaborative innovation data from Korean ICT firms. Using an agent-based model, I expe ...

‘One Size Does Not Fit All’: A Roadmap of Purpose-Driven Mixed-Method Pathways for Sensitivity Analysis of Agent-Based Models
By: Arika Ligmann-Zielinska, Peer-Olaf Siebers, Nicholas Magliocca, Dawn C. Parker, Volker Grimm, Jing Du, Martin Cenek, Viktoriia Radchuk, Nazia N. Arbab, Sheng Li, Uta Berger, Rajiv Paudel, Derek T. Robinson, Piotr Jankowski, Li An, Xinyue Ye, Volume 23 (1)
Abstract: Designing, implementing, and applying agent-based models (ABMs) requires a structured approach, part of which is a comprehensive analysis of the output to input variability in the form of uncertainty and sensitivity analysis (SA). The objective of this paper is to assist in choosing, for a given ABM, the most appropriate methods of SA. We argue that no single SA method fits all ABMs and that different methods of SA should be used based on the overarching purpose of the model. For example, abstract exploratory models that focus on a deeper understanding of the target system and its properties a ...

The Use of Surrogate Models to Analyse Agent-Based Models
By: Guus ten Broeke, George van Voorn, Arend Ligtenberg, Jaap Molenaar, Volume 24 (2)
Abstract: The utility of Agent Based Models (ABMs) for decision making support as well as for scientific applications can be increased considerably by the availability and use of methodologies for thorough model behaviour analysis. In view of their intrinsic construction, ABMs have to be analysed numerically. Furthermore, ABM behaviour is often complex, featuring strong non-linearities, tipping points, and adaptation. This easily leads to high computational costs, presenting a serious practical limitation. Model developers and users alike would benefit from methodologies that can explore large parts of ...

Dynamics of Public Opinion: Diverse Media and Audiences’ Choices
By: Zhongtian Chen, Hanlin Lan, Volume 24 (2)
Abstract: Studies on the fundamental role of diverse media in the evolution of public opinion can protect us from the spreading of brainwashing, extremism, and terrorism. Many fear the information cocoon may result in polarization of the public opinion. Hence, in this work, we investigate how audiences' choices among diverse media might influence public opinion. Specifically, we aim to figure out how peoples' horizons (i.e., range of available media) and quantity, as well as the distribution of media, may shape the space of public opinion. We propose a novel model of opinion dynamics that considers diff ...

No Free Lunch when Estimating Simulation Parameters
By: Ernesto Carrella, Volume 24 (2)
Abstract: In this paper, we have estimated the parameters of 41 simulation models to find which of 9 estimation algorithms performs better. Unfortunately, no single algorithm was the best for all or even most of the models. Rather, five main results emerge from this research. First, each algorithm was the best estimator for at least one parameter. Second, the best estimation algorithm varied not only between models but even between parameters of the same model. Third, each estimation algorithm failed to estimate at least one identifiable parameter. Fourth, choosing the right algorithm improved estimatio ...