Abstract
Save for some special cases, current training methods for Generative Adversarial Networks (GANs) are at best guaranteed to converge to a ‘local Nash equilibrium’ (LNE). Such LNEs, however, can be arbitrarily far from an actual Nash equilibrium (NE), which implies that there are no guarantees on the quality of the found generator or classifier. This paper proposes to model GANs explicitly as finite games in mixed strategies, thereby ensuring that every LNE is an NE. We use the Parallel Nash Memory as a solution method, which is proven to monotonically converge to a resource-bounded Nash equilibrium. We empirically demonstrate that our method is less prone to typical GAN problems such as mode collapse and produces solutions that are less exploitable than those produced by GANs and MGANs.
Original language | English |
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Title of host publication | Artificial Intelligence |
Subtitle of host publication | 30th Benelux Conference, BNAIC 2018, Revised Selected Papers |
Editors | Martin Atzmueller, Wouter Duivesteijn |
Place of Publication | Cham |
Publisher | Springer |
Pages | 73-89 |
Number of pages | 17 |
ISBN (Electronic) | 978-3-030-31978-6 |
ISBN (Print) | 978-3-030-31977-9 |
DOIs | |
Publication status | Published - 2019 |
Event | 30th Benelux Conference on Artificial Intelligence, BNAIC 2018 - ‘s-Hertogenbosch, Netherlands Duration: 8 Nov 2018 → 9 Nov 2018 |
Publication series
Name | Communications in Computer and Information Science |
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Volume | 1021 |
ISSN (Print) | 1865-0929 |
ISSN (Electronic) | 1865-0937 |
Conference
Conference | 30th Benelux Conference on Artificial Intelligence, BNAIC 2018 |
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Country/Territory | Netherlands |
City | ‘s-Hertogenbosch |
Period | 8/11/18 → 9/11/18 |
Bibliographical note
Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-careOtherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.