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Trajectory-Dominant Pareto Optimization for Intelligence
π‘Explains AI stagnation via Pareto traps in trajectory spaceβessential for scaling adaptive intelligence (87 chars)
β‘ 30-Second TL;DR
What Changed
Formulates intelligence as multi-objective trajectory optimization
Why It Matters
Shifts AI progress focus from scaling to escaping geometric optimization traps, potentially unlocking long-horizon adaptability. Offers tools like TEDI for diagnosing stagnation in RL and developmental systems.
What To Do Next
Download arXiv:2602.13230v1 and compute TEDI on your RL agent's trajectories to detect traps.
Who should care:Researchers & Academics
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Original source: ArXiv AI β