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 |
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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