Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/257529 
Authors: 
Year of Publication: 
2021
Citation: 
[Journal:] Games [ISSN:] 2073-4336 [Volume:] 12 [Issue:] 2 [Article No.:] 47 [Publisher:] MDPI [Place:] Basel [Year:] 2021 [Pages:] 1-11
Publisher: 
MDPI, Basel
Abstract: 
Successful algorithms have been developed for computing Nash equilibrium in a variety of finite game classes. However, solving continuous games - in which the pure strategy space is (potentially uncountably) infinite - is far more challenging. Nonetheless, many real-world domains have continuous action spaces, e.g., where actions refer to an amount of time, money, or other resource that is naturally modeled as being real-valued as opposed to integral. We present a new algorithm for approximating Nash equilibrium strategies in continuous games. In addition to two-player zero-sum games, our algorithm also applies to multiplayer games and games with imperfect information. We experiment with our algorithm on a continuous imperfect-information Blotto game, in which two players distribute resources over multiple battlefields. Blotto games have frequently been used to model national security scenarios and have also been applied to electoral competition and auction theory. Experiments show that our algorithm is able to quickly compute close approximations of Nash equilibrium strategies for this game.
Subjects: 
Blotto game
continuous game
imperfect information
national security
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
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