Reviews: Monte-Carlo Tree Search for Constrained POMDPs

Neural Information Processing Systems 

This paper addresses a potentially important problem by giving an algorithm that can solve large constrained POMDPs with online methods. A constrained POMDP, which augments a traditional POMDP with multi-attribute cost constraints, is an important extension that can help model a wider range of real-world phenomena than a POMDP can. Having such an algorithm for solving large CPOMDPs is a very valuable contribution. The authors provide, in this paper, a derivation of an unconstrained objective to be solved (resulting from taking the dual of the CPOMDP's linear program), backed by theoretical justification, and an adaptation of the online search algorithm, POMCP, that incorporates cost constraints by approximately optimizing the objective. The paper is extremely well-written, free of typos, and clear in its presentation.