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

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

MIT researchers: Sometimes, it might be better to train a robot in an environment that's different from the one where it will be deployed.

This seems to be a property property of the reinforcement learning problem.

When both AI agents explore mostly the same areas, the agent trained in the non-noisy environment performs better.

This might occur because the agent needs to understand patterns it can't learn in the noise-free environment.

The researchers hope to explore how the indoor training effect might occur in more complex reinforcement learning environments.

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