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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2406.00741 |
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| _version_ | 1866929369893568512 |
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| author | Paolini, Giovanni Moreschini, Lorenzo Veneziano, Francesco Iraci, Alessandro |
| author_facet | Paolini, Giovanni Moreschini, Lorenzo Veneziano, Francesco Iraci, Alessandro |
| contents | This paper introduces ZeusAI, an artificial intelligence system developed to play the board game 7 Wonders Duel. Inspired by the AlphaZero reinforcement learning algorithm, ZeusAI relies on a combination of Monte Carlo Tree Search and a Transformer Neural Network to learn the game without human supervision. ZeusAI competes at the level of top human players, develops both known and novel strategies, and allows us to test rule variants to improve the game's balance. This work demonstrates how AI can help in understanding and enhancing board games. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_00741 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Learning to Play 7 Wonders Duel Without Human Supervision Paolini, Giovanni Moreschini, Lorenzo Veneziano, Francesco Iraci, Alessandro Artificial Intelligence Machine Learning This paper introduces ZeusAI, an artificial intelligence system developed to play the board game 7 Wonders Duel. Inspired by the AlphaZero reinforcement learning algorithm, ZeusAI relies on a combination of Monte Carlo Tree Search and a Transformer Neural Network to learn the game without human supervision. ZeusAI competes at the level of top human players, develops both known and novel strategies, and allows us to test rule variants to improve the game's balance. This work demonstrates how AI can help in understanding and enhancing board games. |
| title | Learning to Play 7 Wonders Duel Without Human Supervision |
| topic | Artificial Intelligence Machine Learning |
| url | https://arxiv.org/abs/2406.00741 |