Oryx: a Scalable Sequence Model for Many-Agent Coordination in Offline MARL
PositiveArtificial Intelligence
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.
— Curated by the World Pulse Now AI Editorial System

