Stacked Thompson Bandits

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Authors Lenz Belzner, Thomas Gabor
Journal/Conference Name Proceeding - 2017 IEEE/ACM 3rd International Workshop on Software Engineering for Smart Cyber-Physical Systems, SEsCPS 2017
Paper Category
Paper Abstract We introduce Stacked Thompson Bandits (STB) for efficiently generating plans that are likely to satisfy a given bounded temporal logic requirement. STB uses a simulation for evaluation of plans, and takes a Bayesian approach to using the resulting information to guide its search. In particular, we show that stacking multiarmed bandits and using Thompson sampling to guide the action selection process for each bandit enables STB to generate plans that satisfy requirements with a high probability while only searching a fraction of the search space.
Date of publication 2017
Code Programming Language Python

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