  In this paper, we propose a novel algorithm for epistemic planning based on
dynamic epistemic logic (DEL). The novelty is that we limit the depth of
reasoning of the planning agent to an upper bound b, meaning that the planning
agent can only reason about higher-order knowledge to at most (modal) depth b.
The algorithm makes use of a novel type of canonical b-bisimulation contraction
guaranteeing unique minimal models with respect to b-bisimulation. We show our
depth-bounded planning algorithm to be sound. Additionally, we show it to be
complete with respect to planning tasks having a solution within bound b of
reasoning depth (and hence the iterative bound-deepening variant is complete in
the standard sense). For bound b of reasoning depth, the algorithm is shown to
be (b + 1)-EXPTIME complete, and furthermore fixed-parameter tractable in the
number of agents and atoms. We present both a tree search and a graph search
variant of the algorithm, and we benchmark an implementation of the tree search
version against a baseline epistemic planner.
