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| URI | http://purl.tuc.gr/dl/dias/03D9D3AA-40E8-43D1-9E56-2BFCAF875CC6 | - |
| Αναγνωριστικό | http://ebooks.iospress.nl/publication/44941 | - |
| Αναγνωριστικό | https://doi.org/10.3233/978-1-61499-672-9-1604 | - |
| Γλώσσα | en | - |
| Μέγεθος | 2 pages | en |
| Τίτλος | Employing hypergraphs for efficient coalition formation with application to the V2G problem | en |
| Δημιουργός | Christianos Filippos | en |
| Δημιουργός | Χριστιανος Φιλιππος | el |
| Δημιουργός | Chalkiadakis Georgios | en |
| Δημιουργός | Χαλκιαδακης Γεωργιος | el |
| Εκδότης | IOS Press | en |
| Περίληψη | This paper proposes, for the first time in the literature, the use of hypergraphs for the efficient formation of effective coalitions. We put forward several formation methods that build on existing hypergraph algorithms, and exploit hypergraph structure to identify agents with desirable characteristics. Our approach allows the near-instantaneous formation of high quality coalitions, while adhering to multiple stated requirements regarding coalition quality. Moreover, our methods are shown to scale to dozens of thousands of agents within fractions of a second; with one of them scaling to even millions of agents within seconds. We apply our approach to the problem of forming coalitions to provide (electric) vehicle-to-grid (V2G) services. Ours is the first approach able to deal with large-scale, realtime coalition formation for the V2G problem, while taking multiple criteria into account for creating electric vehicle coalitions. | en |
| Τύπος | Πλήρης Δημοσίευση σε Συνέδριο | el |
| Τύπος | Conference Full Paper | en |
| Άδεια Χρήσης | http://creativecommons.org/licenses/by/4.0/ | en |
| Ημερομηνία | 2018-10-30 | - |
| Ημερομηνία Δημοσίευσης | 2016 | - |
| Θεματική Κατηγορία | Efficient coalition formation | en |
| Θεματική Κατηγορία | V2G problem | en |
| Βιβλιογραφική Αναφορά | F. Christianos and G. Chalkiadakis, "Employing hypergraphs for efficient coalition formation with application to the V2G problem," in 22nd European Conference on Artificial Intelligence, 2016, pp. 1604-1605. doi: 10.3233/978-1-61499-672-9-1604 | en |
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