Mechanical conscience is proposed as a trajectory-level regulatory filter for AI policies that reduces cumulative deviation from admissible regions, with claimed theoretical properties and extension to multi-agent settings.
Shielded reinforcement learning under dynamic temporal logic constraints
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Mechanical Conscience: A Mathematical Framework for Dependability of Machine Intelligence
Mechanical conscience is proposed as a trajectory-level regulatory filter for AI policies that reduces cumulative deviation from admissible regions, with claimed theoretical properties and extension to multi-agent settings.