Ιδρυματικό Αποθετήριο
Πολυτεχνείο Κρήτης
Πολυτεχνείο Κρήτης
EN
|
EL
| URI | http://purl.tuc.gr/dl/dias/5D424E06-FF5A-4384-B4DF-969BF8EA1952 | - |
| Αναγνωριστικό | https://dl.acm.org/citation.cfm?id=3238054 | - |
| Γλώσσα | en | - |
| Μέγεθος | 3 pages | en |
| Τίτλος | Overlapping coalition formation via probabilistic topic modeling | en |
| Δημιουργός | Mamakos Michail | en |
| Δημιουργός | Μαμακος Μιχαηλ | el |
| Δημιουργός | Chalkiadakis Georgios | en |
| Δημιουργός | Χαλκιαδακης Γεωργιος | el |
| Εκδότης | International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS) | en |
| Περίληψη | Research in cooperative games often assumes that agents know the coalitional values with certainty, and that they can belong to one coalition only. By contrast, this work assumes that the value of a coalition is based on an underlying collaboration structure emerging due to existing but unknown relations among the agents; and that agents can form overlapping coalitions. Specifically, we first propose Relational Rules, a novel representation scheme for cooperative games with overlapping coalitions, which encodes the aforementioned relations, and which extends the well-known MC-nets representation to this setting. We then present a novel decisionmaking method for decentralized overlapping coalition formation, which exploits probabilistic topic modeling-and, in particular, online Latent Dirichlet Allocation. By interpreting formed coalitions as documents, agents can effectively learn topics that correspond to profitable collaboration structures. | en |
| Τύπος | Σύντομη Δημοσίευση σε Συνέδριο | el |
| Τύπος | Conference Short Paper | en |
| Άδεια Χρήσης | http://creativecommons.org/licenses/by/4.0/ | en |
| Ημερομηνία | 2019-10-11 | - |
| Ημερομηνία Δημοσίευσης | 2018 | - |
| Θεματική Κατηγορία | Game theory | en |
| Θεματική Κατηγορία | Multi agent systems | en |
| Θεματική Κατηγορία | Statistics | en |
| Βιβλιογραφική Αναφορά | M. Mamakos and G. Chalkiadakis, "Overlapping coalition formation via probabilistic topic modeling," in 17th International Conference on Autonomous Agents and Multiagent Systems, 2018., pp. 2010-2012. | en |
Copyright © DIAS 2013
