Computational Model Library

Displaying 10 of 1070 results for "Elena A. Pearce" clear search

The model aims at estimating household energy consumption and the related greenhouse gas (GHG) emissions reduction based on the behavior of the individual household under different operationalizations of the Theory of Planned Behaviour (TPB).
The original model is developed as a tool to explore households decisions regarding solar panel investments and cumulative consequences of these individual choices (i.e. diffusion of PVs, regional emissions savings, monetary savings). We extend the model to explore a methodological question regarding an interpretation of qualitative concepts from social science theories, specifically Theory of Planned Behaviour in a formal code of quantitative agent-based models (ABMs). We develop 3 versions of the model: one TPB-based ABM designed by the authors and two alternatives inspired by the TPB-ABM of Schwarz and Ernst (2009) and the TPB-ABM of Rai and Robinson (2015). The model is implemented in NetLogo.

This ABM re-implements and extends the simulation model of peer review described in Squazzoni & Gandelli (Squazzoni & Gandelli, 2013 - doi:10.18564/jasss.2128) (hereafter: ‘SG’). The SG model was originally developed for NetLogo and is also available in CoMSES at this link.
The purpose of the original SG model was to explore how different author and reviewer strategies would impact the outcome of a journal peer review system on an array of dimensions including peer review efficacy, efficiency and equality. In SG, reviewer evaluation consists of a continuous variable in the range [0,1], and this evaluation scale is the same for all reviewers. Our present extension to the SG model allows to explore the consequences of two more realistic assumptions on reviewer evaluation: (1) that the evaluation scale is discrete (e.g. like in a Likert scale); (2) that there may be differences among their interpretation of the grades of the evaluation scale (i.e. that the grade language is heterogeneous).

We study cultural dissemination in the context of an Axelrod-like agent-based model describing the spread of cultural traits across a society, with an added element of social influence. This modification produces absorbing states exhibiting greater variation in number and size of distinct cultural regions compared to the original Axelrod model, and we identify the mechanism responsible for this amplification in heterogeneity. We develop several new metrics to quantitatively characterize the heterogeneity and geometric qualities of these absorbing states. Additionally, we examine the dynamical approach to absorbing states in both our Social Influence Model as well as the Axelrod Model, which not only yields interesting insights into the differences in behavior of the two models over time, but also provides a more comprehensive view into the behavior of Axelrod’s original model. The quantitative metrics introduced in this paper have broad potential applicability across a large variety of agent-based cultural dissemination models.

ergodicity_test

Jakob Grazzini | Published Monday, November 29, 2010 | Last modified Saturday, April 27, 2013

This Python module contain a function that is able to test the ergodicity of a given agent based model. It is sufficient to produce one long time series and many smaller time series. The function uses

Tyche

Tony Lawson | Published Tuesday, February 28, 2012 | Last modified Saturday, April 27, 2013

Demographic microsimulation model used in speed tests against LIAM 2.

Feedback Loop Example: Vegetation Patch Growth

James Millington | Published Thursday, December 20, 2012 | Last modified Saturday, April 27, 2013

This model illustrates a positive ‘growth’ feedback loop in which the areal extent of an entity increases through time.

Societal Simulator v203 fertility graph fix

Tim Gooding | Published Wednesday, November 26, 2014

This is the same model as used in the article ‘Modelling Society’s Evolutionary Forces’ except the Fertility graph has been corrected. The Fertility graph was not used in the published article.

Multistate modeling extended by behavioral rules

Frans Willekens Sabine Zinn Matthias Leuchter Anna Klabunde | Published Wednesday, August 03, 2016 | Last modified Tuesday, March 13, 2018

Toolkit to specify demographic multistate model with a behavioural element linking intentions to behaviour

PoliSEA represents a continuous policy process cycle, integrated with the dynamics of a fishery social-ecological system. The policy process in the model is represented by interactions between policymakers and interest groups and subsequent voting during which policymaker decide to increase or decrease the fishing quota for the next season. Policymakers’ positions can be influenced by lobbying of interest groups or interest group coalitions. The quota adopted through the policy process determines the amount of fish that can be harvested from the fish population during the season.

NarcoLogic

Nicholas Magliocca | Published Thursday, August 29, 2019

Investigate spatial adaptive behaviors of narco-trafficking networks in response to various counterdrug interdiction strategies within the cocaine transit zone of Central America and associated maritime areas. Through the novel application of the ‘complex adaptive systems’ paradigm, we implement a potentially transformative coupled agent-based and interdiction optimization modeling approach to compellingly demonstrate: (a) how current efforts to disrupt narco-trafficking networks are in fact making them more widespread, resilient, and economically powerful; (b) the potential for alternative interdiction approaches to weaken and contain traffickers.

Displaying 10 of 1070 results for "Elena A. Pearce" clear search

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