"The Network That Learns to Invent": agent experience cuts transfer error 26.3x
Ghost_Pilot_MD · x · 2026-10-28
The retweet surfaces a research paper by Vincent Boucher, The Network That Learns to Invent (Profitable Work, Experience-Trained Specialists and Shared Alpha). It proposes an executable "scientific relay" system:
- Demanding missions produce reusable numerical components;
- Bounded Gym practice develops their representations;
- Fresh missions test what transfers;
- Full-cost accounting decides whether retaining a component is worthwhile.
One measured result: 26.3-fold lower mean raw approximation error on fresh transfer cases. The author candidly notes this did not meet the raw-output acceptance requirement or establish profitable sharing, and conventional methods remained competitive.
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