2019
DESPOT-Alpha: Online POMDP Planning with Large State and Observation Spaces
RSS 2019poster
State-of-the-art sampling-based online POMDP solvers compute near-optimal policies for POMDPs with very large state spaces. However, when faced with large observation spaces, they may become overly optimistic and compute sub-optimal policies, because of particle divergence. This paper presents a new…