Peer reviewing in participatory guarantee systems: Modelisation and algorithmic aspects
The term Participatory Guarantee Systems (PGS) refers to quality certification systems based on the active participation of stakeholders, i.e., producers, consumers, and experts. Unlike to the more common Third Party Certification system, quality standards are guaranteed by peer review: visits of production sites by producers themselves. A critical issue in PGS is the assignment of the peers carrying each review visit, in a way that incentivizes participation. This paper explores algorithmic aspects of this peer assignment, so as to better address challenges faced by PGS. First, we propose a mathematical model of this task that can express diverse local PGS situations, as well as possible extensions. Then, we show that this model leads to computationally challenging problems and identify restrictions that are easy to handle. Finally, we develop an encoding of the model in Answer Set Programming and use it to solve realistic scenarios of PGS.
| Main Authors: | , , , |
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| Format: | conference_item biblioteca |
| Language: | eng |
| Published: |
IFAAMAS
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| Online Access: | http://agritrop.cirad.fr/604524/ http://agritrop.cirad.fr/604524/3/Barrot%20et%20al.%20-%202020%20-%20Peer%20Reviewing%20in%20Participatory%20Guarantee%20Systems.pdf |
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| Summary: | The term Participatory Guarantee Systems (PGS) refers to quality certification systems based on the active participation of stakeholders, i.e., producers, consumers, and experts. Unlike to the more common Third Party Certification system, quality standards are guaranteed by peer review: visits of production sites by producers themselves. A critical issue in PGS is the assignment of the peers carrying each review visit, in a way that incentivizes participation. This paper explores algorithmic aspects of this peer assignment, so as to better address challenges faced by PGS. First, we propose a mathematical model of this task that can express diverse local PGS situations, as well as possible extensions. Then, we show that this model leads to computationally challenging problems and identify restrictions that are easy to handle. Finally, we develop an encoding of the model in Answer Set Programming and use it to solve realistic scenarios of PGS. |
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