An approach for finding optimal schedulers via reinforcement learning in nondeterministic Hybrid Petri nets with general transitions is implemented on the schedulingML branch and for models including non-linear ODES on dynamicapprox.
An approach for finding optimal schedulers via reinforcement learning in nondeterministic Hybrid Petri nets with general transitions is implemented on the schedulingML branch and for models including non-linear ODES on dynamicapprox.
Model checking properties can be maximized and minimized (usage similar to **check** but with keyword **maximize**/**minimize**)
Model checking properties can be maximized and minimized (usage similar to **check** but with keyword **maximize**/**minimize**)
