Harmonized benchmarking of expert-guided RL methods on continuous control tasks surfaces three failure modes and produces a testable decision rule for method selection keyed on expert quality, task termination, and perturbation type.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD) , year =
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When (and How) to Trust the Expert: Diagnosing Query-Time Expert-Guided Reinforcement Learning
Harmonized benchmarking of expert-guided RL methods on continuous control tasks surfaces three failure modes and produces a testable decision rule for method selection keyed on expert quality, task termination, and perturbation type.