cartpole_run.py File Reference

Namespaces
	kusanagi.examples.cartpole.cartpole_run

Functions
def	kusanagi.examples.cartpole.cartpole_run.signal_handler

Variables
float	kusanagi.examples.cartpole.cartpole_run.dt = 0.1
dictionary	kusanagi.examples.cartpole.cartpole_run.model_parameters = {}
list	kusanagi.examples.cartpole.cartpole_run.x0 = [0,0,0,0]
tuple	kusanagi.examples.cartpole.cartpole_run.S0 = np.eye(4)
list	kusanagi.examples.cartpole.cartpole_run.maxU = [10]
tuple	kusanagi.examples.cartpole.cartpole_run.measurement_noise = np.diag(np.ones(len(x0))*0.01**2)
tuple	kusanagi.examples.cartpole.cartpole_run.plant = Cartpole(model_parameters,x0,S0,dt,measurement_noise)
tuple	kusanagi.examples.cartpole.cartpole_run.draw_cp = CartpoleDraw(plant,0.033)
list	kusanagi.examples.cartpole.cartpole_run.angle_dims = [3]
tuple	kusanagi.examples.cartpole.cartpole_run.policy = RBFPolicy(x0,S0,maxU,10, angle_dims)
dictionary	kusanagi.examples.cartpole.cartpole_run.cost_parameters = {}
tuple	kusanagi.examples.cartpole.cartpole_run.cost = partial(cartpole_loss, params=cost_parameters)
float	kusanagi.examples.cartpole.cartpole_run.T = 4.0
int	kusanagi.examples.cartpole.cartpole_run.J = 30
tuple	kusanagi.examples.cartpole.cartpole_run.learner = PILCO(plant, policy, cost, angle_dims, async_plant=False)
list	kusanagi.examples.cartpole.cartpole_run.X = []
list	kusanagi.examples.cartpole.cartpole_run.Y = []
tuple	kusanagi.examples.cartpole.cartpole_run.n_episodes = len(learner.experience.states)
tuple	kusanagi.examples.cartpole.cartpole_run.x = np.array(learner.experience.states[i])
tuple	kusanagi.examples.cartpole.cartpole_run.u = np.array(learner.experience.actions[i])
tuple	kusanagi.examples.cartpole.cartpole_run.x_ = gTrig_np(x, learner.angle_idims)