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Artificial Generals Intelligence: Mastering Generals.io with Reinforcement Learning

A real-time strategy game environment based on Generals.io is introduced, featuring a competitive baseline agent trained with supervised pre-training and self-play, and equipped with potential-based reward shaping and memory features.

Year
2025
Venue
arXiv 2025
Authors
2
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arxiv.org/abs/2507.06825ARXIV-DEFAULT
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Abstract

We introduce a real-time strategy game environment built on Generals.io, a game that hosts thousands of active players each week across multiple game formats. Our environment is fully compatible with Gymnasium and PettingZoo, capable of running thousands of frames per second on commodity hardware. Our reference agent -- trained with supervised pre-training and self-play -- hits the top 0.003% of the 1v1 human leaderboard after just 36 hours on a single H100 GPU. To accelerate learning, we incorporate potential-based reward shaping and memory features. Our contributions -- a modular RTS benchmark and a competitive, state-of-the-art baseline agent -- provide an accessible yet challenging platform for advancing multi-agent reinforcement learning research.

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2