A policy-based RL agent plays a 20 questions game to recommend optimal cybersecurity education and explain the decision by eliciting the minimal set of evidential facts needed to justify defensive actions.
Learning -to-Ask: Knowledge Acquisition via 20 Questions
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Learning-to-Explain through 20Q Gaming: An Explainable Recommender for Cybersecurity Education
A policy-based RL agent plays a 20 questions game to recommend optimal cybersecurity education and explain the decision by eliciting the minimal set of evidential facts needed to justify defensive actions.