Abstract
This letter studies formal synthesis of control policies for continuous-state MDPs. In the quest to satisfy complex combinations of probabilistic temporal logic specifications, we derive a robust linear program for policy synthesis that is solved on a finite-state approximation of the system and is then refined back to a policy for the original system. This linear programming approach leverages occupation measures and enables the multi-objective optimizations needed to handle more complex probabilistic specifications.
| Original language | English |
|---|---|
| Article number | 9291398 |
| Pages (from-to) | 1765-1770 |
| Number of pages | 6 |
| Journal | IEEE Control Systems Letters |
| Volume | 5 |
| Issue number | 5 |
| DOIs | |
| Publication status | Published - Nov 2021 |
Keywords
- Approximate simulation relations
- formal synthesis
- robust linear programming
- stochastic systems
- temporal logic