The proposed method can be extended to handle uncertainties in the system model by incorporating probabilistic models or Bayesian techniques to account for imperfect information about the component failure probabilities. One approach could be to introduce probabilistic distributions for the failure probabilities of the system components, allowing for a more realistic representation of uncertainty. Bayesian inference methods can then be used to update these probabilities as new information becomes available. By incorporating these uncertainties into the model, the policy synthesis algorithm can adapt and make decisions based on the most likely scenarios given the available information.