AI agents trained in simulations that differ from the environments where they are deployed sometimes perform better than agents trained and deployed in the same environment, MIT research shows.

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Researchers from MIT and other institutions discovered that AI agents sometimes perform better when trained in completely noiseless environments compared to noisy ones. This phenomenon, termed the 'indoor training effect,' challenges the conventional practice of matching training and deployment environments. It was observed across various Atari games and suggests new directions for AI training methods, potentially leading to more robust AI performance in uncertain real-world conditions.

New training approach could help AI agents perform better in uncertain conditions