TrajectoryRL subnet 11
TrajectoryRL positions Subnet 11 around improving the behavior and cost profile of AI agents. Official sources describe an open skill factory where distributed compute and reinforcement learning are used to produce stronger agent skills. The subnet is best framed as a competitive environment for optimizing agent trajectories, policies, and task performance rather than a generic chat model network.
About TrajectoryRL subnet 11
TrajectoryRL is an agent-skill subnet using reinforcement learning and competition to improve AI agent trajectories.
AI agents can be expensive, brittle, and unsafe without systematic optimization of the trajectories that drive their behavior.
AI agent developers, RL researchers, open-model builders, validators, and miners interested in policy optimization.
Team and ownership
TrajectoryRL has limited public team detail. Ning Ren is listed as co-founder on an ecosystem explorer; no reliable public location or previous-experience source was found.
- Ning Ren, Co-Founder, TrajectoryRL
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