Improved Reinforcement Learning in Asymmetric Real-time Strategy Games via Strategy Diversity.
- Resource Type
- Article
- Authors
- Dasgupta, Prithviraj; Kliem, John
- Source
- International Journal of Serious Games; Mar2023, Vol. 10 Issue 1, p19-38, 20p
- Subject
- STRATEGY games
REINFORCEMENT learning
MACHINE learning
RULES of games
ARTIFICIAL intelligence
- Language
- ISSN
- 23848766
Copyright of International Journal of Serious Games is the property of Serious Games Society and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)