Parallelizing Exploration-Exploitation Tradeoffs with Gaussian Process Bandit Optimization

@article{Desautels2012ParallelizingET,
  title={Parallelizing Exploration-Exploitation Tradeoffs with Gaussian Process Bandit Optimization},
  author={Thomas Desautels and Andreas Krause and Joel W. Burdick},
  journal={Journal of Machine Learning Research},
  year={2012},
  volume={15},
  pages={3873-3923}
}
Can one parallelize complex exploration– exploitation tradeoffs? As an example, consider the problem of optimal highthroughput experimental design, where we wish to sequentially design batches of experiments in order to simultaneously learn a surrogate function mapping stimulus to response and identify the maximum of the function. We formalize the task as a multiarmed bandit problem, where the unknown payoff function is sampled from a Gaussian process (GP), and instead of a single arm, in each… CONTINUE READING
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Gaussian process optimization in the bandit setting: No regret and experimental design

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  • In ICML,
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