An On-Line POMDP Solver for Continuous Observation Spaces
Marcus Hoerger,Hanna Kurniawati,Marcus Hoerger,Hanna Kurniawati
Planning under partial obervability is essential for autonomous robots. A principled way to address such planning problems is the Partially Observable Markov Decision Process (POMDP). Although solving POMDPs is computationally intractable, substantial advancements have been achieved in developing approximate POMDP solvers in the past two decades. However, computing robust solutions for problems wi...
