Safe POMDP online planning via shielding
Partially observable Markov decision processes (POMDPs) have been widely used in many robotic applications for sequential decision-making under uncertainty. POMDP online planning algorithms such as Partially Observable Monte-Carlo Planning (POMCP) can solve very large POMDPs with the goal of maximiz...
| Egile Nagusiak: | , , |
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| Formatua: | Conference item |
| Hizkuntza: | English |
| Argitaratua: |
IEEE
2024
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