# Here wedefineour bandits.Forthis example weareusinga four-armed bandit. The pullBanditfunctiongenerates a random numberfroma normal distributionwitha meanof0.The lower the bandit number, the more likely a positive reward will be returned. We want our agenttolearntoalways choose the bandit that...
Two-Armed BanditFeatures Mary Yockey, a second-place winner at the 1997 NPC National Fitness Championships. How she became interested in bodybuilding; Her biceps and triceps routine; Self-assessment on her physique.Vallejo, DorisJoe Weiders Muscle & F...
We obtain minimax lower bounds on the regret for the classical two-armed bandit problem. We provide a finite-sample minimax version of the well-known log n asymptotic lower bound of Lai and Robbins (1985). Also, in contrast to the log n asymptotic results on the regret, we show that the...
Some Remarks on the Two-Armed Bandit Abstract In this paper we consider the following situation: An experimenter has to perform a total of N trial on two Bernoulli-type experiments E1and E2with success probabilites α and β respectively, where both α and β are unknown to him. Received N...
Suppose the arms of a two-armed bandit generate i.i.d. Bernoulli random variables with success probabilities ρ and λ respectively. It is desired to maximize the expected sum of N trials where N is fixed. If the prior distribution of (ρ, λ) is concentrated at two points (a, b) and...
ICSE'22 - Havoc-MAB: Enhancing AFL havoc mutation with Two-layer Multi-Armed Bandit - Tricker-z/havoc-mab
We consider the two-armed bandit problem in the following robust (minimax) setting. Distributions of rewards corresponding to the first arm have known finite mathematical expectation. Distributions of rewards corresponding to the second arm are normal ones with unknown mathematical expectation and unit ...
We consider two agents playing simultaneously the same stochastic three-armed bandit problem. The two agents are cooperating but they cannot communicate. We propose a strategy with no collisions at all between the players (with very high probability), and with near-optimal regret O(Tlog(T))...
The two-armed bandit is one of the simplest possible non-deterministic control environments which are not trivial. And yet it is astonishingly difficult to control. For the finite-time problem, dynamic programming methods provide optimal controllers. Optimal control strategies also exist for the infini...
We consider exponential two-armed bandit problem in which losses are described by exponential probability distribution densities. The results may be applied to queueing systems in which two alternative modes of server operation are available. One has to determine the mode corresponding to the smaller ...