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Found 2 papers, 1 papers with code
SubIQ: Inverse Soft-Q Learning for Offline Imitation with Suboptimal Demonstrations
Most of the existing offline IL methods developed for this setting are based on behavior cloning or distribution matching, where the aim is to match the occupancy distribution of the imitation policy with that of the expert policy.
Imitate the Good and Avoid the Bad: An Incremental Approach to Safe Reinforcement Learning
In an exhaustive set of experiments, we demonstrate that our approach is able to outperform top benchmark approaches for solving Constrained RL problems, with respect to expected cost, CVaR cost, or even unknown cost constraints.
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