Motivation Large crowd navigation with sudden changes: unlikely events are out of likely sample. So, we want to bring in another distribution based on importance and not likelyness. Goals retains DESPOT garantees outperforms DESPOT and POMCP DESPOT with Importance Sampling take our initial belief sample trajectories according to Importance Sampling distribution calculate values of those states obtain value estimate based on weighted average of the values Importance Sampling of trajectories We define an importance distribution of some trajectory \xi:
\begin{equation} q(\xi | b,\pi) = q(s_0) \prod_{t=0}^{D} q(s_{t+1}, o_{t+1} | s_{t}, a_{t+1}) \end{equation}
Background Importance Sampling