2 citations · 2 across the 1 of their papers we have counts for
2 papers
cs.AI2021★ 2 cited
Simplified Belief-Dependent Reward MCTS Planning with Guaranteed Tree Consistency
Ori Sztyglic, Andrey Zhitnikov, Vadim Indelman
Partially Observable Markov Decision Processes (POMDPs) are notoriously hard to solve. Most advanced state-of-the-art online solvers leverage ideas of Monte Carlo Tree Search (MCTS…
cs.AI2021
Online POMDP Planning via Simplification
Ori Sztyglic, Vadim Indelman
In this paper, we consider online planning in partially observable domains. Solving the corresponding POMDP problem is a very challenging task, particularly in an online setting. O…