  The problem of Multi-agent Path Finding (MAPF) consists in providing agents
with efficient paths while preventing collisions. Numerous solvers have been
developed so far since MAPF is critical for practical applications such as
automated warehouses. The recently-proposed Priority Inheritance with
Backtracking (PIBT) is a promising decoupled method that solves MAPF
iteratively with flexible priorities. The method is aimed to be decentralized
and has a very low computational cost, but it is shortsighted in the sense that
it plans only one step ahead, thus occasionally resulting in inefficient
plannings. This work proposes a generalization of PIBT, called windowed PIBT
(winPIBT), that introduces a configurable time window. winPIBT allows agents to
plan paths anticipating multiple steps ahead. We prove that, similarly to PIBT,
all agents reach their own destinations in finite time as long as the
environment is a graph with adequate properties, e.g., biconnected.
Experimental results over various scenarios confirm that winPIBT mitigates
livelock situations occurring in PIBT, and usually plans more efficient paths
given adequate window size.
