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Table 1 Weight vectors for different RL policies

From: Inverse reinforcement learning for intelligent mechanical ventilation and sedative dosing in intensive care units

Policy Weight of reward function
π BL [1/7,1/7,1/7,1/7,1/7,1/7,1/7]
\(\phantom {\dot {i}\!}\pi _{{BL}_{1}}\) [0.14,0.24,0.15,0.19,0.07,0.07,0.14]
\(\phantom {\dot {i}\!}\pi _{{BL}_{2}}\) [0.08,0.17,0.16,0.18,0.29,0.10,0.02]
\(\phantom {\dot {i}\!}\pi _{{BL}_{3}}\) [0.07,0.19,0.12,0.21,0.26,0.04,0.11]