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On the identification and mitigation of weaknesses in the Knowledge Gradient policy for multi armed bandits

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Figure

Figure 1: Mean percentage of lost reward compared to the GI policy for five policies forthe Bernoulli MAB with uniform priors andwhile on the right γ ∈ [0.9, 0.99]
Figure 2: Percentage lost reward relative to the GI policy for six policies for the BernoulliMAB with α = 1, β∈ [1, 10] and γ = 0.98
Figure 4: Mean percentage of lost reward compared to the KG policy for three policesfor the Exponential MAB with Gamma(2,3) priors and γ ∈ [0.9, 0.99]
Figure 5: The left plot shows RLB values for KG and GI policies for γ = 0.95, n1 = 1,µ1 = 0
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