Metamodels for evaluating, calibrating and applying agent-based models : a review
The recent advancement of agent-based modeling is characterized by higher demands on the pa-rameterization, evaluation and documentation of these computationally expensive models. Accordingly, there is also a growing request for “easy to go” applications just mimicking the input-output behavior of s...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Pietzsch, Bruno - 1990- [verfasserIn] Fiedler, Sebastian [verfasserIn] Mertens, Kai Gustav [verfasserIn] Richter, Markus [verfasserIn] Scherer, Cédric [verfasserIn] Widyastuti, Kirana [verfasserIn] Wimmler, Marie-Christin [verfasserIn] Zakharova, Liubov - 1985- [verfasserIn] Berger, Uta - 1962- [verfasserIn] |
|---|---|
| Körperschaften: |
Technische Universität Hamburg Technische Universität Hamburg, Institut für Controlling und Simulation |
| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
31-03-2020 |
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| Rechteinformationen: |
Open Access Urheberrechtsschutz 1.0 |
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| Schlagwörter: |
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| Anmerkung: |
Sonstige Körperschaft: Technische Universität Hamburg Sonstige Körperschaft: Technische Universität Hamburg, Institut für Controlling und Simulation |
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| Umfang: |
Diagramme |
| Übergeordnetes Werk: |
Enthalten in: The Journal of academic social science studies - Elazığ : Fırat Üniversitesi, 2008, 23(2020), 2, Artikel-ID 9, Seite 1-12 |
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| Übergeordnetes Werk: |
volume:23 ; year:2020 ; number:2 ; elocationid:9 ; pages:1-12 |
| Links: |
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| DOI / URN: |
urn:nbn:de:gbv:830-882.0104823 10.15480/882.3636 10.18564/jasss.4274 |
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Metamodels for evaluating, calibrating and applying agent-based models a review Bruno Pietzsch, Sebastian Fiedler, Kai G. Mertens, Markus Richter, Cédric Scherer, Kirana Widyastuti, Marie-Christin Wimmler, Liubov Zakharova, Uta Berger |
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metamodels for evaluating, calibrating and applying agent-based modelsa review |
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Metamodels for evaluating, calibrating and applying agent-based models a review |
| abstract |
The recent advancement of agent-based modeling is characterized by higher demands on the pa-rameterization, evaluation and documentation of these computationally expensive models. Accordingly, there is also a growing request for “easy to go” applications just mimicking the input-output behavior of such mod-els. Metamodels are being increasingly used for these tasks. In this paper, we provide an overview of common metamodel types and the purposes of their usage in an agent-based modeling context. To guide modelers in the selection and application of metamodels for their own needs, we further assessed their implementation effort and performance. We performed a literature research in January 2019 using four different databases. Five different terms paraphrasing metamodels (approximation, emulator, meta-model, metamodel and surrogate) were used to capture the whole range of relevant literature in all disciplines. All metamodel applications found were then categorized into specific metamodel types and rated by different junior and senior researches from varying disciplines (including forest sciences, landscape ecology, or economics) regarding the implementation effort and performance. Specifically, we captured the metamodel performance according to (i) the consider-ation of uncertainties, (ii) the suitability assessment provided by the authors for the particular purpose, and (iii) the number of valuation criteria provided for suitability assessment. We selected 40 distinct metamodel applications from studies published in peer-reviewed journals from 2005 to 2019. These were used for the sensitivity analysis, calibration and upscaling of agent-based models, as well to mimic their prediction for different scenarios. This review provides information about the most applicable metamodel types for each purpose and forms a first guidance for the implementation and validation of metamodels for agent-based models. Sonstige Körperschaft: Technische Universität Hamburg Sonstige Körperschaft: Technische Universität Hamburg, Institut für Controlling und Simulation |
| abstractGer |
The recent advancement of agent-based modeling is characterized by higher demands on the pa-rameterization, evaluation and documentation of these computationally expensive models. Accordingly, there is also a growing request for “easy to go” applications just mimicking the input-output behavior of such mod-els. Metamodels are being increasingly used for these tasks. In this paper, we provide an overview of common metamodel types and the purposes of their usage in an agent-based modeling context. To guide modelers in the selection and application of metamodels for their own needs, we further assessed their implementation effort and performance. We performed a literature research in January 2019 using four different databases. Five different terms paraphrasing metamodels (approximation, emulator, meta-model, metamodel and surrogate) were used to capture the whole range of relevant literature in all disciplines. All metamodel applications found were then categorized into specific metamodel types and rated by different junior and senior researches from varying disciplines (including forest sciences, landscape ecology, or economics) regarding the implementation effort and performance. Specifically, we captured the metamodel performance according to (i) the consider-ation of uncertainties, (ii) the suitability assessment provided by the authors for the particular purpose, and (iii) the number of valuation criteria provided for suitability assessment. We selected 40 distinct metamodel applications from studies published in peer-reviewed journals from 2005 to 2019. These were used for the sensitivity analysis, calibration and upscaling of agent-based models, as well to mimic their prediction for different scenarios. This review provides information about the most applicable metamodel types for each purpose and forms a first guidance for the implementation and validation of metamodels for agent-based models. Sonstige Körperschaft: Technische Universität Hamburg Sonstige Körperschaft: Technische Universität Hamburg, Institut für Controlling und Simulation |
| abstract_unstemmed |
The recent advancement of agent-based modeling is characterized by higher demands on the pa-rameterization, evaluation and documentation of these computationally expensive models. Accordingly, there is also a growing request for “easy to go” applications just mimicking the input-output behavior of such mod-els. Metamodels are being increasingly used for these tasks. In this paper, we provide an overview of common metamodel types and the purposes of their usage in an agent-based modeling context. To guide modelers in the selection and application of metamodels for their own needs, we further assessed their implementation effort and performance. We performed a literature research in January 2019 using four different databases. Five different terms paraphrasing metamodels (approximation, emulator, meta-model, metamodel and surrogate) were used to capture the whole range of relevant literature in all disciplines. All metamodel applications found were then categorized into specific metamodel types and rated by different junior and senior researches from varying disciplines (including forest sciences, landscape ecology, or economics) regarding the implementation effort and performance. Specifically, we captured the metamodel performance according to (i) the consider-ation of uncertainties, (ii) the suitability assessment provided by the authors for the particular purpose, and (iii) the number of valuation criteria provided for suitability assessment. We selected 40 distinct metamodel applications from studies published in peer-reviewed journals from 2005 to 2019. These were used for the sensitivity analysis, calibration and upscaling of agent-based models, as well to mimic their prediction for different scenarios. This review provides information about the most applicable metamodel types for each purpose and forms a first guidance for the implementation and validation of metamodels for agent-based models. Sonstige Körperschaft: Technische Universität Hamburg Sonstige Körperschaft: Technische Universität Hamburg, Institut für Controlling und Simulation |
| url |
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Fiedler, Sebastian Mertens, Kai Gustav Richter, Markus Scherer, Cédric Widyastuti, Kirana Wimmler, Marie-Christin Zakharova, Liubov 1985- Berger, Uta 1962- Technische Universität Hamburg Technische Universität Hamburg Institut für Controlling und Simulation |
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Fiedler, Sebastian Mertens, Kai Gustav Richter, Markus Scherer, Cédric Widyastuti, Kirana Wimmler, Marie-Christin Zakharova, Liubov 1985- Berger, Uta 1962- Technische Universität Hamburg Technische Universität Hamburg Institut für Controlling und Simulation |
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urn:nbn:de:gbv:830-882.0104823 urn 10.15480/882.3636 doi 10.18564/jasss.4274 doi 11420/7319 hdl (DE-627)1762787067 (DE-599)KXP1762787067 DE-627 ger DE-627 rda eng 330: Wirtschaft Pietzsch, Bruno 1990- verfasserin (DE-588)1047635860 (DE-627)778717070 (DE-576)401438430 aut Metamodels for evaluating, calibrating and applying agent-based models a review Bruno Pietzsch, Sebastian Fiedler, Kai G. Mertens, Markus Richter, Cédric Scherer, Kirana Widyastuti, Marie-Christin Wimmler, Liubov Zakharova, Uta Berger 31-03-2020 Diagramme Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Sonstige Körperschaft: Technische Universität Hamburg Sonstige Körperschaft: Technische Universität Hamburg, Institut für Controlling und Simulation DE-830 Open Access Controlled Vocabulary for Access Rights http://purl.org/coar/access_right/c_abf2 The recent advancement of agent-based modeling is characterized by higher demands on the pa-rameterization, evaluation and documentation of these computationally expensive models. Accordingly, there is also a growing request for “easy to go” applications just mimicking the input-output behavior of such mod-els. Metamodels are being increasingly used for these tasks. In this paper, we provide an overview of common metamodel types and the purposes of their usage in an agent-based modeling context. To guide modelers in the selection and application of metamodels for their own needs, we further assessed their implementation effort and performance. We performed a literature research in January 2019 using four different databases. Five different terms paraphrasing metamodels (approximation, emulator, meta-model, metamodel and surrogate) were used to capture the whole range of relevant literature in all disciplines. All metamodel applications found were then categorized into specific metamodel types and rated by different junior and senior researches from varying disciplines (including forest sciences, landscape ecology, or economics) regarding the implementation effort and performance. Specifically, we captured the metamodel performance according to (i) the consider-ation of uncertainties, (ii) the suitability assessment provided by the authors for the particular purpose, and (iii) the number of valuation criteria provided for suitability assessment. We selected 40 distinct metamodel applications from studies published in peer-reviewed journals from 2005 to 2019. These were used for the sensitivity analysis, calibration and upscaling of agent-based models, as well to mimic their prediction for different scenarios. This review provides information about the most applicable metamodel types for each purpose and forms a first guidance for the implementation and validation of metamodels for agent-based models. DE-830 Urheberrechtsschutz 1.0 rs http://rightsstatements.org/vocab/InC/1.0/ calibration DSpace emulator DSpace individual-based model DSpace review DSpace sensitivity analysis DSpace surrogate model DSpace calibration (dpeaa)DE-206 emulator (dpeaa)DE-206 individual-based model (dpeaa)DE-206 review (dpeaa)DE-206 sensitivity analysis (dpeaa)DE-206 surrogate model (dpeaa)DE-206 Fiedler, Sebastian verfasserin aut Mertens, Kai Gustav verfasserin (DE-588)1217213260 (DE-627)1728978459 aut Richter, Markus verfasserin aut Scherer, Cédric verfasserin (DE-588)1202528708 (DE-627)1686674600 aut Widyastuti, Kirana verfasserin aut Wimmler, Marie-Christin verfasserin aut Zakharova, Liubov 1985- verfasserin (DE-588)1222289997 (DE-627)1741315611 aut Berger, Uta 1962- verfasserin (DE-588)1151471143 (DE-627)1011823357 (DE-576)497806118 aut Technische Universität Hamburg (DE-588)1112763473 (DE-627)866918418 (DE-576)476770564 oth Technische Universität Hamburg Institut für Controlling und Simulation (DE-588)1127155229 (DE-627)881587400 (DE-576)485090678 oth Enthalten in The Journal of academic social science studies Elazığ : Fırat Üniversitesi, 2008 23(2020), 2, Artikel-ID 9, Seite 1-12 Online-Ressource (DE-627)1662576935 (DE-600)2967863-8 2147-2971 nnns volume:23 year:2020 number:2 elocationid:9 pages:1-12 https://doi.org/10.18564/jasss.4274 Resolving-System http://nbn-resolving.de/urn:nbn:de:gbv:830-882.0104823 Resolving-System kostenfrei https://doi.org/10.15480/882.3636 Resolving-System kostenfrei http://hdl.handle.net/11420/7319 Resolving-System kostenfrei GBV_USEFLAG_U GBV_ILN_23 ISIL_DE-830 SYSFLAG_1 GBV_KXP GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2086 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 GBV_ILN_26 GBV_ILN_2403 GBV_ILN_26 ISIL_DE-206 GBV_ILN_2403 ISIL_DE-LFER DSpace AR 23 2020 2 9 1-12 045F 330: Wirtschaft 23 01 0830 3949557903 tuhh Elektronischer Volltext f z 13-07-21 26 01 0206 395810147X x1z 27-07-21 2403 01 DE-LFER 3963891548 00 --%%-- --%%-- n --%%-- l01 10-08-21 23 01 0830 https://doi.org/10.15480/882.3636 LF 2403 01 DE-LFER https://doi.org/10.15480/882.3636 2403 01 DE-LFER http://nbn-resolving.de/urn:nbn:de:gbv:830-882.0104823 23 01 0830 tuhh 23 01 0830 tubdok |
| spelling |
urn:nbn:de:gbv:830-882.0104823 urn 10.15480/882.3636 doi 10.18564/jasss.4274 doi 11420/7319 hdl (DE-627)1762787067 (DE-599)KXP1762787067 DE-627 ger DE-627 rda eng 330: Wirtschaft Pietzsch, Bruno 1990- verfasserin (DE-588)1047635860 (DE-627)778717070 (DE-576)401438430 aut Metamodels for evaluating, calibrating and applying agent-based models a review Bruno Pietzsch, Sebastian Fiedler, Kai G. Mertens, Markus Richter, Cédric Scherer, Kirana Widyastuti, Marie-Christin Wimmler, Liubov Zakharova, Uta Berger 31-03-2020 Diagramme Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Sonstige Körperschaft: Technische Universität Hamburg Sonstige Körperschaft: Technische Universität Hamburg, Institut für Controlling und Simulation DE-830 Open Access Controlled Vocabulary for Access Rights http://purl.org/coar/access_right/c_abf2 The recent advancement of agent-based modeling is characterized by higher demands on the pa-rameterization, evaluation and documentation of these computationally expensive models. Accordingly, there is also a growing request for “easy to go” applications just mimicking the input-output behavior of such mod-els. Metamodels are being increasingly used for these tasks. In this paper, we provide an overview of common metamodel types and the purposes of their usage in an agent-based modeling context. To guide modelers in the selection and application of metamodels for their own needs, we further assessed their implementation effort and performance. We performed a literature research in January 2019 using four different databases. Five different terms paraphrasing metamodels (approximation, emulator, meta-model, metamodel and surrogate) were used to capture the whole range of relevant literature in all disciplines. All metamodel applications found were then categorized into specific metamodel types and rated by different junior and senior researches from varying disciplines (including forest sciences, landscape ecology, or economics) regarding the implementation effort and performance. Specifically, we captured the metamodel performance according to (i) the consider-ation of uncertainties, (ii) the suitability assessment provided by the authors for the particular purpose, and (iii) the number of valuation criteria provided for suitability assessment. We selected 40 distinct metamodel applications from studies published in peer-reviewed journals from 2005 to 2019. These were used for the sensitivity analysis, calibration and upscaling of agent-based models, as well to mimic their prediction for different scenarios. This review provides information about the most applicable metamodel types for each purpose and forms a first guidance for the implementation and validation of metamodels for agent-based models. DE-830 Urheberrechtsschutz 1.0 rs http://rightsstatements.org/vocab/InC/1.0/ calibration DSpace emulator DSpace individual-based model DSpace review DSpace sensitivity analysis DSpace surrogate model DSpace calibration (dpeaa)DE-206 emulator (dpeaa)DE-206 individual-based model (dpeaa)DE-206 review (dpeaa)DE-206 sensitivity analysis (dpeaa)DE-206 surrogate model (dpeaa)DE-206 Fiedler, Sebastian verfasserin aut Mertens, Kai Gustav verfasserin (DE-588)1217213260 (DE-627)1728978459 aut Richter, Markus verfasserin aut Scherer, Cédric verfasserin (DE-588)1202528708 (DE-627)1686674600 aut Widyastuti, Kirana verfasserin aut Wimmler, Marie-Christin verfasserin aut Zakharova, Liubov 1985- verfasserin (DE-588)1222289997 (DE-627)1741315611 aut Berger, Uta 1962- verfasserin (DE-588)1151471143 (DE-627)1011823357 (DE-576)497806118 aut Technische Universität Hamburg (DE-588)1112763473 (DE-627)866918418 (DE-576)476770564 oth Technische Universität Hamburg Institut für Controlling und Simulation (DE-588)1127155229 (DE-627)881587400 (DE-576)485090678 oth Enthalten in The Journal of academic social science studies Elazığ : Fırat Üniversitesi, 2008 23(2020), 2, Artikel-ID 9, Seite 1-12 Online-Ressource (DE-627)1662576935 (DE-600)2967863-8 2147-2971 nnns volume:23 year:2020 number:2 elocationid:9 pages:1-12 https://doi.org/10.18564/jasss.4274 Resolving-System http://nbn-resolving.de/urn:nbn:de:gbv:830-882.0104823 Resolving-System kostenfrei https://doi.org/10.15480/882.3636 Resolving-System kostenfrei http://hdl.handle.net/11420/7319 Resolving-System kostenfrei GBV_USEFLAG_U GBV_ILN_23 ISIL_DE-830 SYSFLAG_1 GBV_KXP GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2086 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 GBV_ILN_26 GBV_ILN_2403 GBV_ILN_26 ISIL_DE-206 GBV_ILN_2403 ISIL_DE-LFER DSpace AR 23 2020 2 9 1-12 045F 330: Wirtschaft 23 01 0830 3949557903 tuhh Elektronischer Volltext f z 13-07-21 26 01 0206 395810147X x1z 27-07-21 2403 01 DE-LFER 3963891548 00 --%%-- --%%-- n --%%-- l01 10-08-21 23 01 0830 https://doi.org/10.15480/882.3636 LF 2403 01 DE-LFER https://doi.org/10.15480/882.3636 2403 01 DE-LFER http://nbn-resolving.de/urn:nbn:de:gbv:830-882.0104823 23 01 0830 tuhh 23 01 0830 tubdok |
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urn:nbn:de:gbv:830-882.0104823 urn 10.15480/882.3636 doi 10.18564/jasss.4274 doi 11420/7319 hdl (DE-627)1762787067 (DE-599)KXP1762787067 DE-627 ger DE-627 rda eng 330: Wirtschaft Pietzsch, Bruno 1990- verfasserin (DE-588)1047635860 (DE-627)778717070 (DE-576)401438430 aut Metamodels for evaluating, calibrating and applying agent-based models a review Bruno Pietzsch, Sebastian Fiedler, Kai G. Mertens, Markus Richter, Cédric Scherer, Kirana Widyastuti, Marie-Christin Wimmler, Liubov Zakharova, Uta Berger 31-03-2020 Diagramme Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Sonstige Körperschaft: Technische Universität Hamburg Sonstige Körperschaft: Technische Universität Hamburg, Institut für Controlling und Simulation DE-830 Open Access Controlled Vocabulary for Access Rights http://purl.org/coar/access_right/c_abf2 The recent advancement of agent-based modeling is characterized by higher demands on the pa-rameterization, evaluation and documentation of these computationally expensive models. Accordingly, there is also a growing request for “easy to go” applications just mimicking the input-output behavior of such mod-els. Metamodels are being increasingly used for these tasks. In this paper, we provide an overview of common metamodel types and the purposes of their usage in an agent-based modeling context. To guide modelers in the selection and application of metamodels for their own needs, we further assessed their implementation effort and performance. We performed a literature research in January 2019 using four different databases. Five different terms paraphrasing metamodels (approximation, emulator, meta-model, metamodel and surrogate) were used to capture the whole range of relevant literature in all disciplines. All metamodel applications found were then categorized into specific metamodel types and rated by different junior and senior researches from varying disciplines (including forest sciences, landscape ecology, or economics) regarding the implementation effort and performance. Specifically, we captured the metamodel performance according to (i) the consider-ation of uncertainties, (ii) the suitability assessment provided by the authors for the particular purpose, and (iii) the number of valuation criteria provided for suitability assessment. We selected 40 distinct metamodel applications from studies published in peer-reviewed journals from 2005 to 2019. These were used for the sensitivity analysis, calibration and upscaling of agent-based models, as well to mimic their prediction for different scenarios. This review provides information about the most applicable metamodel types for each purpose and forms a first guidance for the implementation and validation of metamodels for agent-based models. DE-830 Urheberrechtsschutz 1.0 rs http://rightsstatements.org/vocab/InC/1.0/ calibration DSpace emulator DSpace individual-based model DSpace review DSpace sensitivity analysis DSpace surrogate model DSpace calibration (dpeaa)DE-206 emulator (dpeaa)DE-206 individual-based model (dpeaa)DE-206 review (dpeaa)DE-206 sensitivity analysis (dpeaa)DE-206 surrogate model (dpeaa)DE-206 Fiedler, Sebastian verfasserin aut Mertens, Kai Gustav verfasserin (DE-588)1217213260 (DE-627)1728978459 aut Richter, Markus verfasserin aut Scherer, Cédric verfasserin (DE-588)1202528708 (DE-627)1686674600 aut Widyastuti, Kirana verfasserin aut Wimmler, Marie-Christin verfasserin aut Zakharova, Liubov 1985- verfasserin (DE-588)1222289997 (DE-627)1741315611 aut Berger, Uta 1962- verfasserin (DE-588)1151471143 (DE-627)1011823357 (DE-576)497806118 aut Technische Universität Hamburg (DE-588)1112763473 (DE-627)866918418 (DE-576)476770564 oth Technische Universität Hamburg Institut für Controlling und Simulation (DE-588)1127155229 (DE-627)881587400 (DE-576)485090678 oth Enthalten in The Journal of academic social science studies Elazığ : Fırat Üniversitesi, 2008 23(2020), 2, Artikel-ID 9, Seite 1-12 Online-Ressource (DE-627)1662576935 (DE-600)2967863-8 2147-2971 nnns volume:23 year:2020 number:2 elocationid:9 pages:1-12 https://doi.org/10.18564/jasss.4274 Resolving-System http://nbn-resolving.de/urn:nbn:de:gbv:830-882.0104823 Resolving-System kostenfrei https://doi.org/10.15480/882.3636 Resolving-System kostenfrei http://hdl.handle.net/11420/7319 Resolving-System kostenfrei GBV_USEFLAG_U GBV_ILN_23 ISIL_DE-830 SYSFLAG_1 GBV_KXP GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2086 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 GBV_ILN_26 GBV_ILN_2403 GBV_ILN_26 ISIL_DE-206 GBV_ILN_2403 ISIL_DE-LFER DSpace AR 23 2020 2 9 1-12 045F 330: Wirtschaft 23 01 0830 3949557903 tuhh Elektronischer Volltext f z 13-07-21 26 01 0206 395810147X x1z 27-07-21 2403 01 DE-LFER 3963891548 00 --%%-- --%%-- n --%%-- l01 10-08-21 23 01 0830 https://doi.org/10.15480/882.3636 LF 2403 01 DE-LFER https://doi.org/10.15480/882.3636 2403 01 DE-LFER http://nbn-resolving.de/urn:nbn:de:gbv:830-882.0104823 23 01 0830 tuhh 23 01 0830 tubdok |
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urn:nbn:de:gbv:830-882.0104823 urn 10.15480/882.3636 doi 10.18564/jasss.4274 doi 11420/7319 hdl (DE-627)1762787067 (DE-599)KXP1762787067 DE-627 ger DE-627 rda eng 330: Wirtschaft Pietzsch, Bruno 1990- verfasserin (DE-588)1047635860 (DE-627)778717070 (DE-576)401438430 aut Metamodels for evaluating, calibrating and applying agent-based models a review Bruno Pietzsch, Sebastian Fiedler, Kai G. Mertens, Markus Richter, Cédric Scherer, Kirana Widyastuti, Marie-Christin Wimmler, Liubov Zakharova, Uta Berger 31-03-2020 Diagramme Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Sonstige Körperschaft: Technische Universität Hamburg Sonstige Körperschaft: Technische Universität Hamburg, Institut für Controlling und Simulation DE-830 Open Access Controlled Vocabulary for Access Rights http://purl.org/coar/access_right/c_abf2 The recent advancement of agent-based modeling is characterized by higher demands on the pa-rameterization, evaluation and documentation of these computationally expensive models. Accordingly, there is also a growing request for “easy to go” applications just mimicking the input-output behavior of such mod-els. Metamodels are being increasingly used for these tasks. In this paper, we provide an overview of common metamodel types and the purposes of their usage in an agent-based modeling context. To guide modelers in the selection and application of metamodels for their own needs, we further assessed their implementation effort and performance. We performed a literature research in January 2019 using four different databases. Five different terms paraphrasing metamodels (approximation, emulator, meta-model, metamodel and surrogate) were used to capture the whole range of relevant literature in all disciplines. All metamodel applications found were then categorized into specific metamodel types and rated by different junior and senior researches from varying disciplines (including forest sciences, landscape ecology, or economics) regarding the implementation effort and performance. Specifically, we captured the metamodel performance according to (i) the consider-ation of uncertainties, (ii) the suitability assessment provided by the authors for the particular purpose, and (iii) the number of valuation criteria provided for suitability assessment. We selected 40 distinct metamodel applications from studies published in peer-reviewed journals from 2005 to 2019. These were used for the sensitivity analysis, calibration and upscaling of agent-based models, as well to mimic their prediction for different scenarios. This review provides information about the most applicable metamodel types for each purpose and forms a first guidance for the implementation and validation of metamodels for agent-based models. DE-830 Urheberrechtsschutz 1.0 rs http://rightsstatements.org/vocab/InC/1.0/ calibration DSpace emulator DSpace individual-based model DSpace review DSpace sensitivity analysis DSpace surrogate model DSpace calibration (dpeaa)DE-206 emulator (dpeaa)DE-206 individual-based model (dpeaa)DE-206 review (dpeaa)DE-206 sensitivity analysis (dpeaa)DE-206 surrogate model (dpeaa)DE-206 Fiedler, Sebastian verfasserin aut Mertens, Kai Gustav verfasserin (DE-588)1217213260 (DE-627)1728978459 aut Richter, Markus verfasserin aut Scherer, Cédric verfasserin (DE-588)1202528708 (DE-627)1686674600 aut Widyastuti, Kirana verfasserin aut Wimmler, Marie-Christin verfasserin aut Zakharova, Liubov 1985- verfasserin (DE-588)1222289997 (DE-627)1741315611 aut Berger, Uta 1962- verfasserin (DE-588)1151471143 (DE-627)1011823357 (DE-576)497806118 aut Technische Universität Hamburg (DE-588)1112763473 (DE-627)866918418 (DE-576)476770564 oth Technische Universität Hamburg Institut für Controlling und Simulation (DE-588)1127155229 (DE-627)881587400 (DE-576)485090678 oth Enthalten in The Journal of academic social science studies Elazığ : Fırat Üniversitesi, 2008 23(2020), 2, Artikel-ID 9, Seite 1-12 Online-Ressource (DE-627)1662576935 (DE-600)2967863-8 2147-2971 nnns volume:23 year:2020 number:2 elocationid:9 pages:1-12 https://doi.org/10.18564/jasss.4274 Resolving-System http://nbn-resolving.de/urn:nbn:de:gbv:830-882.0104823 Resolving-System kostenfrei https://doi.org/10.15480/882.3636 Resolving-System kostenfrei http://hdl.handle.net/11420/7319 Resolving-System kostenfrei GBV_USEFLAG_U GBV_ILN_23 ISIL_DE-830 SYSFLAG_1 GBV_KXP GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2086 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 GBV_ILN_26 GBV_ILN_2403 GBV_ILN_26 ISIL_DE-206 GBV_ILN_2403 ISIL_DE-LFER DSpace AR 23 2020 2 9 1-12 045F 330: Wirtschaft 23 01 0830 3949557903 tuhh Elektronischer Volltext f z 13-07-21 26 01 0206 395810147X x1z 27-07-21 2403 01 DE-LFER 3963891548 00 --%%-- --%%-- n --%%-- l01 10-08-21 23 01 0830 https://doi.org/10.15480/882.3636 LF 2403 01 DE-LFER https://doi.org/10.15480/882.3636 2403 01 DE-LFER http://nbn-resolving.de/urn:nbn:de:gbv:830-882.0104823 23 01 0830 tuhh 23 01 0830 tubdok |
| allfieldsSound |
urn:nbn:de:gbv:830-882.0104823 urn 10.15480/882.3636 doi 10.18564/jasss.4274 doi 11420/7319 hdl (DE-627)1762787067 (DE-599)KXP1762787067 DE-627 ger DE-627 rda eng 330: Wirtschaft Pietzsch, Bruno 1990- verfasserin (DE-588)1047635860 (DE-627)778717070 (DE-576)401438430 aut Metamodels for evaluating, calibrating and applying agent-based models a review Bruno Pietzsch, Sebastian Fiedler, Kai G. Mertens, Markus Richter, Cédric Scherer, Kirana Widyastuti, Marie-Christin Wimmler, Liubov Zakharova, Uta Berger 31-03-2020 Diagramme Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Sonstige Körperschaft: Technische Universität Hamburg Sonstige Körperschaft: Technische Universität Hamburg, Institut für Controlling und Simulation DE-830 Open Access Controlled Vocabulary for Access Rights http://purl.org/coar/access_right/c_abf2 The recent advancement of agent-based modeling is characterized by higher demands on the pa-rameterization, evaluation and documentation of these computationally expensive models. Accordingly, there is also a growing request for “easy to go” applications just mimicking the input-output behavior of such mod-els. Metamodels are being increasingly used for these tasks. In this paper, we provide an overview of common metamodel types and the purposes of their usage in an agent-based modeling context. To guide modelers in the selection and application of metamodels for their own needs, we further assessed their implementation effort and performance. We performed a literature research in January 2019 using four different databases. Five different terms paraphrasing metamodels (approximation, emulator, meta-model, metamodel and surrogate) were used to capture the whole range of relevant literature in all disciplines. All metamodel applications found were then categorized into specific metamodel types and rated by different junior and senior researches from varying disciplines (including forest sciences, landscape ecology, or economics) regarding the implementation effort and performance. Specifically, we captured the metamodel performance according to (i) the consider-ation of uncertainties, (ii) the suitability assessment provided by the authors for the particular purpose, and (iii) the number of valuation criteria provided for suitability assessment. We selected 40 distinct metamodel applications from studies published in peer-reviewed journals from 2005 to 2019. These were used for the sensitivity analysis, calibration and upscaling of agent-based models, as well to mimic their prediction for different scenarios. This review provides information about the most applicable metamodel types for each purpose and forms a first guidance for the implementation and validation of metamodels for agent-based models. DE-830 Urheberrechtsschutz 1.0 rs http://rightsstatements.org/vocab/InC/1.0/ calibration DSpace emulator DSpace individual-based model DSpace review DSpace sensitivity analysis DSpace surrogate model DSpace calibration (dpeaa)DE-206 emulator (dpeaa)DE-206 individual-based model (dpeaa)DE-206 review (dpeaa)DE-206 sensitivity analysis (dpeaa)DE-206 surrogate model (dpeaa)DE-206 Fiedler, Sebastian verfasserin aut Mertens, Kai Gustav verfasserin (DE-588)1217213260 (DE-627)1728978459 aut Richter, Markus verfasserin aut Scherer, Cédric verfasserin (DE-588)1202528708 (DE-627)1686674600 aut Widyastuti, Kirana verfasserin aut Wimmler, Marie-Christin verfasserin aut Zakharova, Liubov 1985- verfasserin (DE-588)1222289997 (DE-627)1741315611 aut Berger, Uta 1962- verfasserin (DE-588)1151471143 (DE-627)1011823357 (DE-576)497806118 aut Technische Universität Hamburg (DE-588)1112763473 (DE-627)866918418 (DE-576)476770564 oth Technische Universität Hamburg Institut für Controlling und Simulation (DE-588)1127155229 (DE-627)881587400 (DE-576)485090678 oth Enthalten in The Journal of academic social science studies Elazığ : Fırat Üniversitesi, 2008 23(2020), 2, Artikel-ID 9, Seite 1-12 Online-Ressource (DE-627)1662576935 (DE-600)2967863-8 2147-2971 nnns volume:23 year:2020 number:2 elocationid:9 pages:1-12 https://doi.org/10.18564/jasss.4274 Resolving-System http://nbn-resolving.de/urn:nbn:de:gbv:830-882.0104823 Resolving-System kostenfrei https://doi.org/10.15480/882.3636 Resolving-System kostenfrei http://hdl.handle.net/11420/7319 Resolving-System kostenfrei GBV_USEFLAG_U GBV_ILN_23 ISIL_DE-830 SYSFLAG_1 GBV_KXP GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2086 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 GBV_ILN_26 GBV_ILN_2403 GBV_ILN_26 ISIL_DE-206 GBV_ILN_2403 ISIL_DE-LFER DSpace AR 23 2020 2 9 1-12 045F 330: Wirtschaft 23 01 0830 3949557903 tuhh Elektronischer Volltext f z 13-07-21 26 01 0206 395810147X x1z 27-07-21 2403 01 DE-LFER 3963891548 00 --%%-- --%%-- n --%%-- l01 10-08-21 23 01 0830 https://doi.org/10.15480/882.3636 LF 2403 01 DE-LFER https://doi.org/10.15480/882.3636 2403 01 DE-LFER http://nbn-resolving.de/urn:nbn:de:gbv:830-882.0104823 23 01 0830 tuhh 23 01 0830 tubdok |
| language |
English |
| source |
Enthalten in The Journal of academic social science studies 23(2020), 2, Artikel-ID 9, Seite 1-12 volume:23 year:2020 number:2 elocationid:9 pages:1-12 |
| sourceStr |
Enthalten in The Journal of academic social science studies 23(2020), 2, Artikel-ID 9, Seite 1-12 volume:23 year:2020 number:2 elocationid:9 pages:1-12 |
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Article |
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findex.gbv.de |
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23@ 26@1z 2403@01 |
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330: Wirtschaft |
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Pietzsch, Bruno @@aut@@ Fiedler, Sebastian @@aut@@ Mertens, Kai Gustav @@aut@@ Richter, Markus @@aut@@ Scherer, Cédric @@aut@@ Widyastuti, Kirana @@aut@@ Wimmler, Marie-Christin @@aut@@ Zakharova, Liubov @@aut@@ Berger, Uta @@aut@@ |
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