2 papers
cs.LO2024
Policies Grow on Trees: Model Checking Families of MDPs
Roman Andriushchenko, Milan Češka, Sebastian Junges +1
Markov decision processes (MDPs) provide a fundamental model for sequential decision making under process uncertainty. A classical synthesis task is to compute for a given MDP a wi…
cs.LO2023
Search and Explore: Symbiotic Policy Synthesis in POMDPs
Roman Andriushchenko, Alexander Bork, Milan Češka +3
This paper marries two state-of-the-art controller synthesis methods for partially observable Markov decision processes (POMDPs), a prominent model in sequential decision making un…