Simulator

If we have a transition system, it might be nice to run a simulation. In this case, we have an MDP that models a hungry lion. Depending on the state it is in, it needs to decide whether it wants to ‘rawr’ or ‘hunt’ in order to prevent reaching the state ‘dead’.

from stormvogel import *

lion = examples.create_lion_mdp()
show(lion)

<stormvogel.visualization.JSVisualization at 0x7f175c9729c0>

Now, let’s run a simulation of the lion! If we do not provide a scheduling function, then the simulator just does a random walk, taking a random choice each time.

path = simulate_path(lion, steps=5, seed=1234)

We could also provide a scheduling function to choose the actions ourselves. This is somewhat similar to the bird API.

def scheduler(s: State) -> Action:
    return Action("rawr")


path2 = stormvogel.simulator.simulate_path(
    lion, steps=5, seed=1234, scheduler=scheduler
)

We can also use the scheduler to create a partial model. This model contains all the states that have been discovered by the the simulation.

partial_model = stormvogel.simulator.simulate(
    lion, steps=5, scheduler=scheduler, seed=1234
)
show(partial_model)

<stormvogel.visualization.JSVisualization at 0x7f1743af3800>