Zero-knowledge protocols for model checking that certify linear temporal logic properties of hidden systems using ranking functions, polynomial commitments, and sigma protocols.
2008.Principles of model checking
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Shielding the policy improvement process in offline RL yields policies that are safe with high probability while outperforming unshielded baselines in both average and worst-case performance, especially under limited data.
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Zero-Knowledge Model Checking
Zero-knowledge protocols for model checking that certify linear temporal logic properties of hidden systems using ranking functions, polynomial commitments, and sigma protocols.
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Robust Probabilistic Shielding for Safe Offline Reinforcement Learning
Shielding the policy improvement process in offline RL yields policies that are safe with high probability while outperforming unshielded baselines in both average and worst-case performance, especially under limited data.