173 citations · 1.6k across the 132 of their papers we have counts for
Showing cs.AIShow all
2 papers · 1 filter
cs.AI2022★ 12 cited
Optimality Guarantees for Particle Belief Approximation of POMDPs
Michael H. Lim, Tyler J. Becker, Mykel J. Kochenderfer +2
Partially observable Markov decision processes (POMDPs) provide a flexible representation for real-world decision and control problems. However, POMDPs are notoriously difficult to…
cs.AI2021★ 2 cited
Compositional Learning-based Planning for Vision POMDPs
Sampada Deglurkar, Michael H. Lim, Johnathan Tucker +3
The Partially Observable Markov Decision Process (POMDP) is a powerful framework for capturing decision-making problems that involve state and transition uncertainty. However, most…