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01Reinforcement Learning

Our core focus lies in the optimization of Multi-Agent RL (MARL) environments, where emergent cooperation and competition provide the framework for autonomous negotiation protocols.

By leveraging RLOO (Relative Least-Squares Online Optimization), we have achieved a 40% reduction in convergence time for high-dimensional action spaces.

Neural Sync Active

Research Archive

01.04.26

Asynchronous Gradient Descent in Super-Large Scale MARL

Peer Reviewed
12.02.26

Sub-Kelvin Noise Reduction in Hybrid Variational Circuits

Technical Note
28.01.26

Kinematic Stability in Variable Density Fluid Environments

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