Oryx: a Scalable Sequence Model for Many-Agent Coordination in Offline MARL

arXiv — cs.LGFriday, October 31, 2025 at 4:00:00 AM
The introduction of Oryx marks a significant advancement in offline multi-agent reinforcement learning (MARL), tackling the complex challenge of coordinating multiple agents effectively. By integrating the innovative retention-based architecture Sable with a new approach to implicit constraint Q-learning, Oryx offers a promising solution for enhancing cooperation among agents in intricate environments. This development is crucial as it paves the way for more efficient algorithms that can handle real-world applications, making strides in the field of artificial intelligence.
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