  Continuing our preleminary work \cite{knowles14}, we define the
safest-with-sight pathfinding problems and explore its solution using
techniques borrowed from measure-theoretic probability theory. We find a simple
recursive definition for the probability that an ideal pathfinder will select
an edge in a given scenario of an uncertain network where edges have
probabilities of failure and vertices provide "vision" of edges via
lines-of-sight. We propose an approximate solution based on our theoretical
findings that would borrow techniques from approximate dynamic programming.
