Dyna-SAuR learns scalable safety filters and policies from an uncertainty-aware model, cutting failures by two orders of magnitude on CartPole and MuJoCo Walker tasks.
Viability Theory: New Direc- tions
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Presents a simple discrete primer on hierarchical causality that requires causation classes, aggregation operators, and discrete event-time maps to connect actor and agent levels.
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Dyna-Style Safety Augmented Reinforcement Learning: Staying Safe in the Face of Uncertainty
Dyna-SAuR learns scalable safety filters and policies from an uncertainty-aware model, cutting failures by two orders of magnitude on CartPole and MuJoCo Walker tasks.