  A parallel variant of the Tower of Hanoi Puzzle is described herein. Within
this parallel context, two theorems on minimal walks in the state space of
configurations, along with their constructive proofs, are provided. These
proofs are used to describe a {\sl denoising method}: a method for identifying
and eliminating sub-optimal transfers within an arbitrary, valid sequence of
disk configurations (as per the rules of the Puzzle). We discuss potential
applications of this method to hierarchical reinforcement learning.
