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Main Authors: Paolini, Giovanni, Moreschini, Lorenzo, Veneziano, Francesco, Iraci, Alessandro
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2406.00741
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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