Thiele, Jan Christoph

[["dc.bibliographiccitation.firstpage","691"],["dc.bibliographiccitation.issue","6"],["dc.bibliographiccitation.journal","Oikos"],["dc.bibliographiccitation.lastpage","696"],["dc.bibliographiccitation.volume","124"],["dc.contributor.author","Thiele, Jan Christoph"],["dc.contributor.author","Grimm, Volker"],["dc.date.accessioned","2018-11-07T09:56:32Z"],["dc.date.available","2018-11-07T09:56:32Z"],["dc.date.issued","2015"],["dc.description.abstract","There are two major limitations to the potential of computational models in ecology for producing general insights: their design is path-dependent, reflecting different underlying questions, assumptions, and data, and there is too little robustness analysis exploring where the model mechanisms explaining certain observations break down. We here argue that both limitations could be overcome if modellers in ecology would more often replicate existing models, try to break the models, and explore modifications. Replication comprises the re-implementation of an existing model and the replication of its results. Breaking models means to identify under what conditions the mechanisms represented in a model can no longer explain observed phenomena. The benefits of replication include less effort being spent to enter the iterative stage of model development and having more time for systematic robustness analysis. A culture of replication would lead to increased credibility, coherence and efficiency of computational modelling and thereby facilitate theory development."],["dc.identifier.doi","10.1111/oik.02170"],["dc.identifier.isi","000356010600003"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/36975"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.relation.issn","1600-0706"],["dc.relation.issn","0030-1299"],["dc.relation.orgunit","Abteilung Ökoinformatik, Biometrie und Waldwachstum"],["dc.title","Replicating and breaking models: good for you and good for ecology"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.subtype","original_ja"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","480"],["dc.bibliographiccitation.issue","3"],["dc.bibliographiccitation.journal","Methods in Ecology and Evolution"],["dc.bibliographiccitation.lastpage","483"],["dc.bibliographiccitation.volume","3"],["dc.contributor.author","Thiele, Jan C."],["dc.contributor.author","Kurth, Winfried"],["dc.contributor.author","Grimm, Volker"],["dc.date.accessioned","2018-11-07T09:09:50Z"],["dc.date.available","2018-11-07T09:09:50Z"],["dc.date.issued","2012"],["dc.description.abstract","1. NetLogo is a free software platform for implementing individual-based and agent-based models. However, NetLogos support of systematic design, performance and analysis of simulation experiments is limited. The statistics software R includes such support. 2. RNetLogo is an R package that links R and NetLogo: any NetLogo program can be controlled and run from R and model results can be transferred back to R for statistical analyses. RNetLogo includes 16 functions, which are explained and demonstrated in the user manual and tutorial. The design of RNetLogo was inspired by a similar link between Mathematica and NetLogo. 3. RNetLogo is a powerful tool for making individual-based modelling more efficient and less ad hoc. It links two fast growing user communities and constitutes a new interface for integrating descriptive statistical analyses and individual-based modelling."],["dc.identifier.doi","10.1111/j.2041-210X.2011.00180.x"],["dc.identifier.isi","000304902500005"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/26354"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Wiley-blackwell"],["dc.relation.issn","2041-210X"],["dc.title","RNetLogo: an R package for running and exploring individual-based models implemented in NetLogo"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","11"],["dc.bibliographiccitation.issue","3"],["dc.bibliographiccitation.journal","Journal of Artificial Societies and Social Simulation"],["dc.bibliographiccitation.volume","17"],["dc.contributor.author","Thiele, Jan Christoph"],["dc.contributor.author","Kurth, Winfried"],["dc.contributor.author","Grimm, Volker"],["dc.date.accessioned","2018-11-07T09:38:43Z"],["dc.date.available","2018-11-07T09:38:43Z"],["dc.date.issued","2014"],["dc.description.abstract","Agent-based models are increasingly used to address questions regarding real-world phenomena and mechanisms; therefore, the calibration of model parameters to certain data sets and patterns is often needed. Furthermore, sensitivity analysis is an important part of the development and analysis of any simulation model. By exploring the sensitivity of model output to changes in parameters, we learn about the relative importance of the various mechanisms represented in the model and how robust the model output is to parameter uncertainty. These insights foster the understanding of models and their use for theory development and applications. Both steps of the model development cycle require massive repetitions of simulation runs with varying parameter values. To facilitate parameter estimation and sensitivity analysis for agent-based modellers, we show how to use a suite of important established methods. Because NetLogo and R are widely used in agent-based modelling and for statistical analyses, we use a simple model implemented in NetLogo as an example, packages in R that implement the respective methods, and the RNetLogo package, which links R and NetLogo. We briefly introduce each method and provide references for further reading. We then list the packages in R that may be used for implementing the methods, provide short code examples demonstrating how the methods can be applied in R, and present and discuss the corresponding outputs. The Supplementary Material includes full, adaptable code samples for using the presented methods with R and NetLogo. Our overall aim is to make agent-based modellers aware of existing methods and tools for parameter estimation and sensitivity analysis and to provide accessible tools for using these methods. In this way, we hope to contribute to establishing an advanced culture of relating agent-based models to data and patterns observed in real systems and to foster rigorous and structured analyses of agent-based models."],["dc.identifier.isi","000339121300018"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/33127"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.relatedmaterial.fulltext","https://www.jasss.org/17/3/11.html"],["dc.relation.issn","1460-7425"],["dc.relation.orgunit","Abteilung Ökoinformatik, Biometrie und Waldwachstum"],["dc.title","Facilitating Parameter Estimation and Sensitivity Analysis of Agent-Based Models: A Cookbook Using Net Logo and R"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.subtype","original_ja"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","972"],["dc.bibliographiccitation.issue","8"],["dc.bibliographiccitation.journal","Environmental Modelling & Software"],["dc.bibliographiccitation.lastpage","974"],["dc.bibliographiccitation.volume","25"],["dc.contributor.author","Thiele, Jan Christoph"],["dc.contributor.author","Grimm, Volker"],["dc.date.accessioned","2022-01-13T09:09:04Z"],["dc.date.available","2022-01-13T09:09:04Z"],["dc.date.issued","2010"],["dc.identifier.doi","10.1016/j.envsoft.2010.02.008"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/98110"],["dc.relation.issn","1364-8152"],["dc.title","NetLogo meets R: Linking agent-based models with a toolbox for their analysis"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dc.type.subtype","original_ja"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.issue","2"],["dc.bibliographiccitation.journal","Journal of Artificial Societies and Social Simulation"],["dc.bibliographiccitation.volume","23"],["dc.contributor.author","Grimm, Volker"],["dc.contributor.author","Railsback, Steven F."],["dc.contributor.author","Vincenot, Christian E."],["dc.contributor.author","Berger, Uta"],["dc.contributor.author","Gallagher, Cara"],["dc.contributor.author","DeAngelis, Donald L."],["dc.contributor.author","Edmonds, Bruce"],["dc.contributor.author","Ge, Jiaqi"],["dc.contributor.author","Giske, Jarl"],["dc.contributor.author","Groeneveld, Jürgen"],["dc.contributor.author","Johnston, Alice S.A."],["dc.contributor.author","Milles, Alexander"],["dc.contributor.author","Nabe-Nielsen, Jacob"],["dc.contributor.author","Polhill, J. Gareth"],["dc.contributor.author","Radchuk, Viktoriia"],["dc.contributor.author","Rohwäder, Marie-Sophie"],["dc.contributor.author","Stillman, Richard A."],["dc.contributor.author","Thiele, Jan C."],["dc.contributor.author","Ayllón, Daniel"],["dc.date.accessioned","2020-12-10T18:42:49Z"],["dc.date.available","2020-12-10T18:42:49Z"],["dc.date.issued","2020"],["dc.identifier.doi","10.18564/jasss.4259"],["dc.identifier.eissn","1460-7425"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/78099"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-354"],["dc.title","The ODD Protocol for Describing Agent-Based and Other Simulation Models: A Second Update to Improve Clarity, Replication, and Structural Realism"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","3"],["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","Journal of Artificial Societies and Social Simulation"],["dc.bibliographiccitation.volume","20"],["dc.contributor.author","Railsback, Steven"],["dc.contributor.author","Ayllon, Daniel"],["dc.contributor.author","Berger, Uta"],["dc.contributor.author","Grimm, Volker"],["dc.contributor.author","Lytinen, Steven"],["dc.contributor.author","Sheppard, Colin"],["dc.contributor.author","Thiele, Jan Christoph"],["dc.date.accessioned","2018-11-07T10:28:14Z"],["dc.date.available","2018-11-07T10:28:14Z"],["dc.date.issued","2017"],["dc.description.abstract","NetLogo has become a standard platform for agent-based simulation, yet there appears to be widespread belief that it is not suitable for large and complex models due to slow execution. Our experience does not support that belief. NetLogo programs often do run very slowly when written to minimize code length and maximize clarity, but relatively simple and easily tested changes can almost always produce major increases in execution speed. We recommend a five-step process for quantifying execution speed, identifying slow parts of code, and writing faster code. Avoiding or improving agent filtering statements can often produce dramatic speed improvements. For models with extensive initialization methods, reorganizing the setup procedure can reduce the initialization effort in simulation experiments. Programming the same behavior in a different way can sometimes provide order-of-magnitude speed increases. For models in which most agents do nothing on most time steps, discrete event simulation-facilitated by the time extension to NetLogo-can dramatically increase speed. NetLogo's BehaviorSpace tool makes it very easy to conduct multiple-model-run experiments in parallel on either desktop or high performance cluster computers, so even quite slow models can be executed thousands of times. NetLogo also is supported by efficient analysis tools, such as BehaviorSearch and RNetLogo, that can reduce the number of model runs and the effort to set them up for (e.g.) parameterization and sensitivity analysis."],["dc.identifier.doi","10.18564/jasss.3282"],["dc.identifier.isi","000397168100003"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/14405"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/43378"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","PUB_WoS_Import"],["dc.publisher","J A S S S"],["dc.relation.issn","1460-7425"],["dc.rights","Goescholar"],["dc.rights.uri","https://goescholar.uni-goettingen.de/licenses"],["dc.title","Improving Execution Speed of Models Implemented in NetLogo"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]