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We propose an approach to neural network stochastic differential games of mean‐field type and its corresponding stochastic stability analysis by means of adversarial training (aka adversarial attacks). This is a class of data‐driven differential games where the distribution of the variables such as the system states and the decision‐makers' strategies (control inputs) is incorporated into the problem...