The analysis of deep reinforcement learning for dynamic graphical games under artificial intelligence
Abstract This paper explores the use of deep reinforcement learning (DRL) to enable autonomous decision-making and strategy optimization in dynamic graphical games. The proposed approach consists of several key components. First, local performance metrics are defined to reduce computational complexi...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-07-01
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| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-05192-w |
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