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cs.LG2022
Coordinate Ascent for Off-Policy RL with Global Convergence Guarantees
Hsin-En Su, Yen-Ju Chen, Ping-Chun Hsieh +1
We revisit the domain of off-policy policy optimization in RL from the perspective of coordinate ascent. One commonly-used approach is to leverage the off-policy policy gradient to…
cs.LG2022
Q-Pensieve: Boosting Sample Efficiency of Multi-Objective RL Through Memory Sharing of Q-Snapshots
Wei Hung, Bo-Kai Huang, Ping-Chun Hsieh +1
Many real-world continuous control problems are in the dilemma of weighing the pros and cons, multi-objective reinforcement learning (MORL) serves as a generic framework of learnin…