Reviews: Blazing the trails before beating the path: Sample-efficient Monte-Carlo planning

The paper considers an interesting and important problem. The results can be interpreted as a natural combination of the planning algorithm of Busoniou and Munos (2012) with the sampling method of Kearns et al (1999). However, the paper introduces a few more tricks to make this idea work (e.g., balances confidence intervals and uncertainties at different parts of the planning tree). The presentation is quite nice and the authors try to give the intuition behind the choices in designing the algorithm. The clarity could be improved by noting that the MAX part of the algorithm is in fact action elimination for best arm identification (can't you use some of the existing results instead of reproving everything from scratch?).