Computational performance of deep reinforcement learning to find Nash equilibria
Christoph Graf, Viktor Zobernig, Johannes Schmidt, Claude Klöckl
| Year of publication: |
2024
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| Authors: | Graf, Christoph ; Zobernig, Viktor ; Schmidt, Johannes ; Klöckl, Claude |
| Published in: |
Computational economics. - Dordrecht [u.a.] : Springer Science + Business Media B.V., ISSN 1572-9974, ZDB-ID 1477445-8. - Vol. 63.2024, 2, p. 529-576
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| Subject: | Bertrand equilibrium | Competition in uniform price auctions | DDPG | Deep deterministic policy gradient algorithm | Parameter sensitivity analysis | Nash-Gleichgewicht | Nash equilibrium | Auktionstheorie | Auction theory | Algorithmus | Algorithm | Mathematische Optimierung | Mathematical programming |
| Description of contents: | Description [link.springer.com] |
freely available
| Type of publication: | Article |
|---|---|
| Type of publication (narrower categories): | Aufsatz in Zeitschrift ; Article in journal |
| Language: | English |
| Other identifiers: | 10.1007/s10614-022-10351-6 [DOI] |
| Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10014472392