Thompson Sampling in Switching Environments with Bayesian Online Change Point Detection

@article{Mellor2013ThompsonSI,
  title={Thompson Sampling in Switching Environments with Bayesian Online Change Point Detection},
  author={Joseph Charles Mellor and Jonathan L. Shapiro},
  journal={CoRR},
  year={2013},
  volume={abs/1302.3721}
}
Thompson Sampling has recently been shown to be optimal in the Bernoulli Multi-Armed Bandit setting[Kaufmann et al., 2012]. This bandit problem assumes stationary distributions for the rewards. It is often unrealistic to model the real world as a stationary distribution. In this paper we derive and evaluate algorithms using Thompson Sampling for a Switching Multi-Armed Bandit Problem. We propose a Thompson Sampling strategy equipped with a Bayesian change point mechanism to tackle this problem… CONTINUE READING