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Expand Up @@ -4,10 +4,12 @@ @article{vermeulen_social_2021
volume = {24},
issn = {1460-7425},
shorttitle = {Social {Network} {Metric}-{Based} {Interventions}?},
doi = {10.18564/jasss.4571},
number = {3},
journal = {Journal of Artificial Societies and Social Simulation},
author = {Vermeulen, Ben and Müller, Matthias and Pyka, Andreas},
year = {2021},
keywords = {Agent-Based Model, Coronavirus, COVID-19, Epidemic, Policy Laboratory},
pages = {6},
file = {Social Network Metric-Based Interventions?:C\:\\Users\\ac135963\\Zotero\\storage\\YNREPJ6M\\6.html:text/html;Vermeulen et al_2021_Social Network Metric-Based Interventions.pdf:C\:\\Users\\ac135963\\Zotero\\storage\\5VUBUQ7A\\Vermeulen et al_2021_Social Network Metric-Based Interventions.pdf:application/pdf},
}
Expand All @@ -34,30 +36,11 @@ @article{kaffai_modeling_2021
month = oct,
year = {2021},
note = {Publisher: Public Library of Science},
keywords = {Agent-based modeling, COVID 19, Economic agents, Germany, Pandemics, Schools, Simulation and modeling, Surveys},
keywords = {Germany, Surveys, COVID 19, Agent-based modeling, Pandemics, Schools, Simulation and modeling, Economic agents},
pages = {e0259108},
file = {Full Text PDF:C\:\\Users\\ac135963\\Zotero\\storage\\R82AL6AY\\Kaffai und Heiberger - 2021 - Modeling non-pharmaceutical interventions in the C.pdf:application/pdf;Snapshot:C\:\\Users\\ac135963\\Zotero\\storage\\WFSBQWMB\\article.html:text/html},
}

@article{cortez_dynamics_2015,
series = {Complex {Adaptive} {Systems} {San} {Jose}, {CA} {November} 2-4, 2015},
title = {Dynamics of the {Schelling} {Social} {Segregation} {Model} in {Networks}},
volume = {61},
issn = {1877-0509},
url = {https://www.sciencedirect.com/science/article/pii/S1877050915029786},
doi = {10.1016/j.procs.2015.09.148},
abstract = {Thomas C. Schelling introduced a simple mathematical model to address the phenomenon of social segregation as a consequence of a natural evolution of elementary local rules. This model became a good framework to understand how local rules, like the selection of a better neighborhood for life, can produce macro-behaviors, like segregation in a population with different kind of individuals. In this work, with the aid of the Schelling's model, we characterize the dynamical evolution of segregation in random networks; analyze the performance of some segregation indices and the dynamics of this model for various network degrees. Finally, we provide probabilistic arguments to explain quantitatively the behavior of the dynamic of Schelling's segregation model in networks.},
language = {en},
urldate = {2023-04-03},
journal = {Procedia Computer Science},
author = {Cortez, Vasco and Rica, Sergio},
month = jan,
year = {2015},
keywords = {dynamic models., index of segregation, Network, Schelling model, segregation},
pages = {60--65},
file = {ScienceDirect Full Text PDF:C\:\\Users\\ac135963\\Zotero\\storage\\3WFYDRV6\\Cortez und Rica - 2015 - Dynamics of the Schelling Social Segregation Model.pdf:application/pdf;ScienceDirect Snapshot:C\:\\Users\\ac135963\\Zotero\\storage\\NQEEKG4R\\S1877050915029786.html:text/html},
}

@article{jiang_method_2022,
title = {A method to create a synthetic population with social networks for geographically-explicit agent-based models},
volume = {2},
Expand Down Expand Up @@ -192,6 +175,38 @@ @article{kapeller_homophily_2019
file = {Full Text PDF:C\:\\Users\\ac135963\\Zotero\\storage\\DF8TALSK\\Kapeller et al. - 2019 - Homophily in networked agent-based models a metho.pdf:application/pdf;Snapshot:C\:\\Users\\ac135963\\Zotero\\storage\\B2YVYY6C\\s40649-019-0070-5.html:text/html},
}

@article{cortez_dynamics_2015,
series = {Complex {Adaptive} {Systems} {San} {Jose}, {CA} {November} 2-4, 2015},
title = {Dynamics of the {Schelling} {Social} {Segregation} {Model} in {Networks}},
volume = {61},
issn = {1877-0509},
url = {https://www.sciencedirect.com/science/article/pii/S1877050915029786},
doi = {10.1016/j.procs.2015.09.148},
abstract = {Thomas C. Schelling introduced a simple mathematical model to address the phenomenon of social segregation as a consequence of a natural evolution of elementary local rules. This model became a good framework to understand how local rules, like the selection of a better neighborhood for life, can produce macro-behaviors, like segregation in a population with different kind of individuals. In this work, with the aid of the Schelling's model, we characterize the dynamical evolution of segregation in random networks; analyze the performance of some segregation indices and the dynamics of this model for various network degrees. Finally, we provide probabilistic arguments to explain quantitatively the behavior of the dynamic of Schelling's segregation model in networks.},
language = {en},
urldate = {2023-04-03},
journal = {Procedia Computer Science},
author = {Cortez, Vasco and Rica, Sergio},
month = jan,
year = {2015},
keywords = {dynamic models., index of segregation, Network, Schelling model, segregation},
pages = {60--65},
file = {ScienceDirect Full Text PDF:C\:\\Users\\ac135963\\Zotero\\storage\\3WFYDRV6\\Cortez und Rica - 2015 - Dynamics of the Schelling Social Segregation Model.pdf:application/pdf;ScienceDirect Snapshot:C\:\\Users\\ac135963\\Zotero\\storage\\NQEEKG4R\\S1877050915029786.html:text/html},
}

@inproceedings{kazil_utilizing_2020,
address = {Cham},
title = {Utilizing {Python} for {Agent}-{Based} {Modeling}: {The} {Mesa} {Framework}},
isbn = {978-3-030-61255-9},
abstract = {Mesa is an agent-based modeling framework written in Python. Originally started in 2013, it was created to be the go-to tool in for researchers wishing to build agent-based models with Python. Within this paper we present Mesa's design goals, along with its underlying architecture. This includes its core components: 1) the model (Model, Agent, Schedule, and Space), 2) analysis (Data Collector and Batch Runner) and the visualization (Visualization Server and Visualization Browser Page). We then discuss how agent-based models can be created in Mesa. This is followed by a discussion of applications and extensions by other researchers to demonstrate how Mesa design is decoupled and extensible and thus creating the opportunity for a larger decentralized ecosystem of packages that people can share and reuse for their own needs. Finally, the paper concludes with a summary and discussion of future development areas for Mesa.},
booktitle = {Social, {Cultural}, and {Behavioral} {Modeling}},
publisher = {Springer International Publishing},
author = {Kazil, Jackie and Masad, David and Crooks, Andrew},
editor = {Thomson, Robert and Bisgin, Halil and Dancy, Christopher and Hyder, Ayaz and Hussain, Muhammad},
year = {2020},
pages = {308--317},
}

@article{yu_melodie_2023,
title = {Melodie: {Agent}-based {Modeling} in {Python}},
volume = {8},
Expand All @@ -211,17 +226,25 @@ @article{yu_melodie_2023
file = {Yu_Hou_2023_Melodie.pdf:C\:\\Users\\ac135963\\Zotero\\storage\\55M5L6TZ\\Yu_Hou_2023_Melodie.pdf:application/pdf},
}

@inproceedings{kazil_utilizing_2020,
address = {Cham},
title = {Utilizing {Python} for {Agent}-{Based} {Modeling}: {The} {Mesa} {Framework}},
isbn = {978-3-030-61255-9},
abstract = {Mesa is an agent-based modeling framework written in Python. Originally started in 2013, it was created to be the go-to tool in for researchers wishing to build agent-based models with Python. Within this paper we present Mesa's design goals, along with its underlying architecture. This includes its core components: 1) the model (Model, Agent, Schedule, and Space), 2) analysis (Data Collector and Batch Runner) and the visualization (Visualization Server and Visualization Browser Page). We then discuss how agent-based models can be created in Mesa. This is followed by a discussion of applications and extensions by other researchers to demonstrate how Mesa design is decoupled and extensible and thus creating the opportunity for a larger decentralized ecosystem of packages that people can share and reuse for their own needs. Finally, the paper concludes with a summary and discussion of future development areas for Mesa.},
booktitle = {Social, {Cultural}, and {Behavioral} {Modeling}},
publisher = {Springer International Publishing},
author = {Kazil, Jackie and Masad, David and Crooks, Andrew},
editor = {Thomson, Robert and Bisgin, Halil and Dancy, Christopher and Hyder, Ayaz and Hussain, Muhammad},
year = {2020},
pages = {308--317},
@inproceedings{hagberg_exploring_2008,
address = {Pasadena, CA USA},
title = {Exploring {Network} {Structure}, {Dynamics}, and {Function} using {NetworkX}},
doi = {10.25080/tcwv9851},
booktitle = {Proceedings of the 7th {Python} in {Science} {Conference}},
author = {Hagberg, Aric A. and Schult, Daniel A. and Swart, Pieter J.},
editor = {Varoquaux, Gaël and Vaught, Travis and Millman, Jarrod},
year = {2008},
pages = {11 -- 15},
}

@book{amblard_which_2015,
title = {Which models are used in social simulation to generate social networks? a review of 17 years of publications in {JASSS}},
shorttitle = {Which models are used in social simulation to generate social networks?},
author = {Amblard, Frédéric and Bouadjio-Boulic, Audren and Sureda Gutierrez, Carlos and Gaudou, Benoit},
month = dec,
year = {2015},
doi = {10.1109/WSC.2015.7408556},
note = {Pages: 4032},
}

@article{kerr_covasim_2020,
Expand All @@ -241,32 +264,6 @@ @article{kerr_covasim_2020
pages = {2020.05.10.20097469},
}

@book{amblard_which_2015,
title = {Which models are used in social simulation to generate social networks? a review of 17 years of publications in {JASSS}},
shorttitle = {Which models are used in social simulation to generate social networks?},
author = {Amblard, Frédéric and Bouadjio-Boulic, Audren and Sureda Gutierrez, Carlos and Gaudou, Benoit},
month = dec,
year = {2015},
doi = {10.1109/WSC.2015.7408556},
note = {Pages: 4032},
}

@inproceedings{hagberg_exploring_2008,
address = {Pasadena, CA USA},
title = {Exploring {Network} {Structure}, {Dynamics}, and {Function} using {NetworkX}},
booktitle = {Proceedings of the 7th {Python} in {Science} {Conference}},
author = {Hagberg, Aric A. and Schult, Daniel A. and Swart, Pieter J.},
editor = {Varoquaux, Gaël and Vaught, Travis and Millman, Jarrod},
year = {2008},
pages = {11 -- 15},
}

@article{mistry_synthpops_2021,
title = {{SynthPops}: a generative model of human contact networks.},
author = {Mistry, D and Kerr, CC and Abeysuriya, R and Wu, M and Fisher, M and Thompson, A and Skrip, L and Cohen, JA and Althouse, BM},
year = {2021},
}

@misc{wilensky_netlogo_1999,
title = {{NetLogo}},
url = {https://ccl.northwestern.edu/netlogo/},
Expand All @@ -275,3 +272,9 @@ @misc{wilensky_netlogo_1999
year = {1999},
note = {Published: Software},
}

@article{mistry_synthpops_2021,
title = {{SynthPops}: a generative model of human contact networks.},
author = {Mistry, D and Kerr, CC and Abeysuriya, R and Wu, M and Fisher, M and Thompson, A and Skrip, L and Cohen, JA and Althouse, BM},
year = {2021},
}

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