The Partially Observable Markov Decision Process has long been recognized as a rich framework for real-world planning and control problems, especially in robotics. However exact s...
Joelle Pineau, Geoffrey J. Gordon, Sebastian Thrun
Recent developments in grid-based and point-based approximation algorithms for POMDPs have greatly improved the tractability of POMDP planning. These approaches operate on sets of...
Joelle Pineau, Geoffrey J. Gordon, Sebastian Thrun
Recent scaling up of POMDP solvers towards realistic applications is largely due to point-based methods such as PBVI, Perseus, and HSVI, which quickly converge to an approximate so...
Abstract— We present a simple randomized POMDP algorithm for planning with continuous actions in partially observable environments. Our algorithm operates on a set of reachable b...