What does "Noise Injection" mean?

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Noise injection is a technique used to improve how learning agents perform in different environments. When agents are trained to make decisions, they often rely on specific probabilities that describe how changes occur in their environment. However, these probabilities can be incorrect or uncertain in real-world situations.

By adding noise—essentially random variations—to the training environment's transition rules, we can create new versions of that environment. These new versions help test how well the agent can adapt to slight changes and make better decisions. This process is called creating $\delta$-environments.

Interestingly, training an agent in a slightly different environment with noise can sometimes lead to better results than training in the original setting. This counterintuitive finding shows that exposure to varied conditions can enhance the agent's ability to generalize and handle unexpected situations.

Overall, noise injection allows for a more robust training process, helping agents become more flexible and effective in their decision-making tasks across different scenarios.