3 papers
cs.RO2026
VOiLA: Vectorized Online Planning with Learned Diffusion Models for POMDP Agents
Marcus Hoerger, Rishikesh Joshi, Rahul Shome +2
Planning under uncertainty is an essential capability for autonomous robots. The Partially Observable Markov Decision Process (POMDP) provides a powerful framework for such a capab…
cs.RO2025
Vectorized Online POMDP Planning
Marcus Hoerger, Muhammad Sudrajat, Hanna Kurniawati
Planning under partial observability is an essential capability of autonomous robots. The Partially Observable Markov Decision Process (POMDP) provides a powerful framework for pla…
stat.ML2023
A Flow-Based Generative Model for Rare-Event Simulation
Lachlan Gibson, Marcus Hoerger, Dirk Kroese
Solving decision problems in complex, stochastic environments is often achieved by estimating the expected outcome of decisions via Monte Carlo sampling. However, sampling may over…