Say you have a bandit problem where the only feedback is
a) the number of times you pulled arm A
b) the number of times you pulled arm B
c) the sum total reward associated with A and B
on a daily basis. What strategy would you use to obtain the best policy here? I was thinking of just training a linear model where A and B are the inputs and C is the output - this weights would tell us the rate of reward for each arm.