@inproceedings{eyerich-et-al:aaai-2010,
   author = "Patrick Eyerich and Thomas Keller and Malte Helmert",
   title = "High-Quality Policies for the Canadian Traveler's Problem",
   booktitle = "Proceedings of the Twenty-Fourth AAAI Conference on
                  Artificial Intelligence (AAAI)",
   month = "july",
   year = "2010",
   publisher = "AAAI Press",
   pages = "51--58",
   abstract = "We consider the stochastic variant of the Canadian
                  Traveler's Problem, a path planning problem where
                  adverse weather can cause some roads to be
                  untraversable. The agent does not initially know
                  which roads can be used. However, it knows a
                  probability distribution for the weather, and it can
                  observe the status of roads incident to its
                  location. The objective is to find a policy with low
                  expected travel cost.  We introduce and compare
                  several algorithms for the stochastic CTP.  Unlike
                  the optimistic approach most commonly considered in
                  the literature, the new approaches we propose take
                  uncertainty into account explicitly. We show that
                  this property enables them to generate policies of
                  much higher quality than the optimistic one, both
                  theoretically and experimentally."
}