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RESEARCH · CL_30817 · May 13 · 16:02

New algorithm closes sample complexity gap in risk-sensitive RL

Researchers have developed a new algorithm that tightens sample complexity bounds for identifying optimal policies in risk-sensitive reinforcement learning. The work addresses a gap between theoretical lower bounds and …