Adapt Project Environments to Fit ML Agents, Developers Advise
To bridge the gap between excellent RL training performance and poor real-world results, developers suggest a pragmatic approach. Instead of complaining, engineers should actively adapt their project environments to better match the conditions the ML agents were trained in.
2026-07-31 ~ 2026-07-31 · 2 related posts
- An Engineering Trick to Adapt ML Agents for the Real World — gandamu_ml · 2026-07-31
- Instead of Complaining About Agents, Adapt Your Project to Their Training Env — gandamu_ml · 2026-07-31