Summary of Alphadou: High-performance End-to-end Doudizhu Ai Integrating Bidding, by Chang Lei et al.
AlphaDou: High-Performance End-to-End Doudizhu AI Integrating Bidding
by Chang Lei, Huan Lei
First submitted to arxiv on: 14 Jul 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computer Science and Game Theory (cs.GT); Multiagent Systems (cs.MA)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper focuses on developing an artificial intelligence (AI) system capable of playing the complex card game Doudizhu at a level comparable to human experts. The researchers build upon previous work in solving simpler card games like Mahjong and Texas Hold’em, but Doudizhu presents unique challenges due to its vast state/action space and reasoning requirements for competition and cooperation. They modify the Deep Monte Carlo algorithm framework by incorporating reinforcement learning and neural networks to estimate win rates and expectations. This approach enables the AI to perform a full range of tasks in the game, including bidding and cardplay. The trained model achieves state-of-the-art performance in an actual Doudizhu environment. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The researchers created a super smart computer program that can play a really hard card game called Doudizhu. They wanted to make it as good as humans who are experts at the game. It’s like trying to solve a puzzle, but instead of blocks or pieces, you have cards! The game is tricky because players need to think about what their opponent might do and how they can work together. The computer program uses special math tricks and learning from its mistakes to get better and better. It even got really good at playing the whole game, including picking which cards to play and when to make big moves. This is important because it shows that the same ideas could be used for other games that are similar. |
Keywords
» Artificial intelligence » Reinforcement learning
