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Q 1 : Variance The goal of this question is to study the variance of different algorithms for adversarial multiarmed bandits problem experimentally. Consider the

Q1: Variance
The goal of this question is to study the variance of different algorithms for adversarial multiarmed
bandits problem experimentally. Consider the EXP3 and EXP3-IX algorithms that
were discussed in class for this problem. Let the number of arms be 10. At each iteration,
generate a 10 dimensional loss vector where each component is chosen iid from a Beta
distribution with both parameters equal to 5 for all arms except the 10th arm. For the 10th
arm, let the parameters be \alpha =5,\beta =10. Implement both the algorithms and run it for
1000 times for 10,000 iterations each and plot the (pseudo) regrets along with error bars.
Comment on the variance of these two algorithms. (Bonus: what happens to the variance
when you play around with the shape parameters?)

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