ImpRator (Inverse Method for Policy with Reward AbstracT behaviOR) is a prototype implementation to compute parameter valuations in parametric Markov decision processes such that optimal policies remain optimal. In other words, given a Markov Decision Process with parametric weights and a valuation of the parameters leading to an optimal policy, synthesize valuations for the parametric weights such that, for any valuation of the parameters, the optimal policy remains optimal.
- a parametric weighted Markov Decision Process
- a reference valuation for the parameters
- a set of parameter valuations for which the optimal policy remains optimal
- parametric Markov decision processes
- parametric probabilistic systems
- parameter synthesis
- policy iteration
- optimal policy
(Developed in 2008-2010)