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| Content Provider | Springer Nature Link |
|---|---|
| Author | Udumyan, Narine Rouchier, Juliette Ami, Dominique |
| Copyright Year | 2013 |
| Abstract | Overexploitation of renewable resources, and more particularly fisheries, is often driven by the lack of information about the state and dynamics of the resource. A solution to this problem stemming from the resource users is proposed in this paper. We use an agent-based model composed of a bio-economic model of Gordon–Schaefer where agents make choices following a very simple learning model. We modify the Roth–Erev learning model so that agents explain their profit not only by current action but also by past action. This modification radically changes the dynamics of the resource use, which turns out to be sustainable. |
| Starting Page | 199 |
| Ending Page | 231 |
| Page Count | 33 |
| File Format | |
| ISSN | 09277099 |
| Journal | Computational Economics |
| Volume Number | 43 |
| Issue Number | 2 |
| e-ISSN | 15729974 |
| Language | English |
| Publisher | Springer US |
| Publisher Date | 2013-03-20 |
| Publisher Place | Boston |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Natural resources Agent-based simulation Roth–Erev model Incomplete information Bioeconomic model of fishery Economic Theory |
| Content Type | Text |
| Resource Type | Article |
| Subject | Economics, Econometrics and Finance Computer Science Applications |
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