Social preferences in the public goods game–An Agent-Based simulation with EconSim
Using a reinforcement-learning algorithm, we model an agent-based simulation of a public goods game with endogenous punishment institutions. We propose an outcome-based model of social preferences that determines the agent’s utility, contribution, and voting behavior during the learning procedure. C...
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| Published in: | PloS one Vol. 18; no. 3; p. e0282112 |
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| Main Authors: | , , , |
| Format: | Journal Article |
| Language: | English |
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United States
Public Library of Science
15.03.2023
Public Library of Science (PLoS) |
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| ISSN: | 1932-6203, 1932-6203 |
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| Abstract | Using a reinforcement-learning algorithm, we model an agent-based simulation of a public goods game with endogenous punishment institutions. We propose an outcome-based model of social preferences that determines the agent’s utility, contribution, and voting behavior during the learning procedure. Comparing our simulation to experimental evidence, we find that the model can replicate human behavior and we can explain the underlying motives of this behavior. We argue that our approach can be generalized to more complex simulations of human behavior. |
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| AbstractList | Using a reinforcement-learning algorithm, we model an agent-based simulation of a public goods game with endogenous punishment institutions. We propose an outcome-based model of social preferences that determines the agent's utility, contribution, and voting behavior during the learning procedure. Comparing our simulation to experimental evidence, we find that the model can replicate human behavior and we can explain the underlying motives of this behavior. We argue that our approach can be generalized to more complex simulations of human behavior. Using a reinforcement-learning algorithm, we model an agent-based simulation of a public goods game with endogenous punishment institutions. We propose an outcome-based model of social preferences that determines the agent's utility, contribution, and voting behavior during the learning procedure. Comparing our simulation to experimental evidence, we find that the model can replicate human behavior and we can explain the underlying motives of this behavior. We argue that our approach can be generalized to more complex simulations of human behavior.Using a reinforcement-learning algorithm, we model an agent-based simulation of a public goods game with endogenous punishment institutions. We propose an outcome-based model of social preferences that determines the agent's utility, contribution, and voting behavior during the learning procedure. Comparing our simulation to experimental evidence, we find that the model can replicate human behavior and we can explain the underlying motives of this behavior. We argue that our approach can be generalized to more complex simulations of human behavior. |
| Audience | Academic |
| Author | Kesten-Kühne, Janis Bühren, Christoph Hirschmann, Christian Haarde, Jan |
| AuthorAffiliation | 1 Faculty of Sport Science, Ruhr-University Bochum, Bochum, Germany 2 Department of Economics, Clausthal University of Technology, Clausthal-Zellerfeld, Germany Universitat Jaume I Departament d’Economia, SPAIN |
| AuthorAffiliation_xml | – name: 2 Department of Economics, Clausthal University of Technology, Clausthal-Zellerfeld, Germany – name: 1 Faculty of Sport Science, Ruhr-University Bochum, Bochum, Germany – name: Universitat Jaume I Departament d’Economia, SPAIN |
| Author_xml | – sequence: 1 givenname: Christoph orcidid: 0000-0001-6155-3694 surname: Bühren fullname: Bühren, Christoph – sequence: 2 givenname: Jan surname: Haarde fullname: Haarde, Jan – sequence: 3 givenname: Christian surname: Hirschmann fullname: Hirschmann, Christian – sequence: 4 givenname: Janis surname: Kesten-Kühne fullname: Kesten-Kühne, Janis |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/36920889$$D View this record in MEDLINE/PubMed |
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| CitedBy_id | crossref_primary_10_1371_journal_pone_0317061 crossref_primary_10_1007_s10614_024_10751_w |
| Cites_doi | 10.1016/S0165-1765(01)00394-9 10.1086/261868 10.1257/aer.90.1.166 10.1037/dec0000033 10.1162/003355399556151 10.1257/aer.90.4.980 10.1016/j.euroecorev.2021.103862 10.1109/TSMCC.2007.913919 10.1007/978-3-319-70766-2_31 10.1007/978-3-658-30101-9_1 10.1093/rfs/hhi003 10.1016/j.ins.2014.09.029 10.7551/mitpress/1654.001.0001 10.1073/pnas.1102493108 10.1007/s10683-014-9405-0 10.1007/978-3-319-96271-9_1 10.1093/restud/rdt022 10.1037/a0023489 10.1038/nature02043 10.2307/1415413 10.1111/j.1538-4616.2011.00415.x 10.1016/S1574-0021(05)02019-8 10.1209/0295-5075/ac3c8a 10.1016/j.jpubeco.2011.05.001 10.1109/MNET.011.2000368 10.1007/978-3-319-93363-4 10.1111/j.1467-9442.2006.00444.x 10.1016/j.engappai.2008.04.002 10.1016/j.physleta.2020.126965 10.1098/rsif.2014.0935 10.1016/j.jebo.2005.03.008 10.1162/003355302760193904 |
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| Snippet | Using a reinforcement-learning algorithm, we model an agent-based simulation of a public goods game with endogenous punishment institutions. We propose an... |
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| StartPage | e0282112 |
| SubjectTerms | Agent-based models Algorithms Analysis Biology and Life Sciences Computer and Information Sciences Computer Simulation Cooperation Cooperative Behavior Data mining Economic models Economic theory Endowment Experiments Game Theory Games Human acts Human behavior Human subjects Humans Laboratories Machine learning Methods Physical Sciences Preferences Public good Punishment Research and Analysis Methods Self interest Simulation Simulation methods Social Behavior Social Behavior Disorders Social Sciences |
| Title | Social preferences in the public goods game–An Agent-Based simulation with EconSim |
| URI | https://www.ncbi.nlm.nih.gov/pubmed/36920889 https://www.proquest.com/docview/2787181167 https://www.proquest.com/docview/2787213212 https://pubmed.ncbi.nlm.nih.gov/PMC10016715 https://doaj.org/article/3d8272f6342643c1bdd6b3e887c24a94 http://dx.doi.org/10.1371/journal.pone.0282112 |
| Volume | 18 |
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