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Table 1 Percentage of risk-prone trajectories based on two decision criteria

From: Learning search polices from humans in a partially observable context

 

Greedy

GMM

Hybrid

Coastal

Human

Risk-prone (f)

77%

11%

30%

46%

26%

Risk-prone (r)

78%

12%

24%

45%

7%

  1. Two decision criteria: the feature (f) and the risk (r) (information gain) metrics.