def __init__(self, representation,
filename=default_location, epsilon=0.1, seed=1):
super(SwimmerPolicy, self).__init__(representation, seed)
E = loadmat(filename)["E"]
self.locs = E["Locs"][0][0]
self.nlocs = E["Nlocs"][0][0]
self.scale = E["scale"][0][0]
self.gains = E["Gains"][0][0]
self.d = 3
self.eGreedy = False
self.epsilon = epsilon
d = self.d
# incidator variables for angles in a state representation
self.angles = np.zeros(2 + self.d * 2 + 1, dtype=np.bool)
self.angles[2:2 + self.d - 1] = True
self.actions = cartesian((d - 1) * [[-2., 0., 2]])
self.actions_num = len(self.actions)
def __init__(self, d=3, k1=7.5, k2=0.3):
"""
d:
number of joints
"""
self.d = d
self.k1 = k1
self.k2 = k2
self.nose = 0
self.masses = np.ones(d)
self.lengths = np.ones(d)
self.inertia = self.masses * self.lengths * self.lengths / 12.
self.goal = np.zeros(2)
# reward function parameters
self.cu = 0.04
self.cx = 2.
Q = np.eye(self.d, k=1) - np.eye(self.d)
Q[-1, :] = self.masses
A = np.eye(self.d, k=1) + np.eye(self.d)
A[-1, -1] = 0.
self.P = old_div(np.dot(np.linalg.inv(Q), A * self.lengths[None, :]), 2.)
self.U = np.eye(self.d) - np.eye(self.d, k=-1)
self.U = self.U[:, :-1]
self.G = np.dot(self.P.T * self.masses[None, :], self.P)
# incidator variables for angles in a state representation
self.angles = np.zeros(2 + self.d * 2 + 1, dtype=np.bool)
self.angles[2:2 + self.d - 1] = True
self.angles[-self.d - 2:] = True
self.actions = cartesian((d - 1) * [[-2., 0., 2]])
self.actions_num = len(self.actions)
self.statespace_limits = [[-15, 15]] * 2 + [[-np.pi, np.pi]] * (d - 1) \
+ [[-2, 2]] * 2 + [[-np.pi * 2, np.pi * 2]] * d
self.statespace_limits = np.array(self.statespace_limits)
self.continuous_dims = list(range(self.statespace_limits.shape[0]))
super(Swimmer, self).__init__()
def __init__(self, d=3, k1=7.5, k2=0.3):
"""
d:
number of joints
"""
self.d = d
self.k1 = k1
self.k2 = k2
self.nose = 0
self.masses = np.ones(d)
self.lengths = np.ones(d)
self.inertia = self.masses * self.lengths * self.lengths / 12.
self.goal = np.zeros(2)
# reward function parameters
self.cu = 0.04
self.cx = 2.
Q = np.eye(self.d, k=1) - np.eye(self.d)
Q[-1, :] = self.masses
A = np.eye(self.d, k=1) + np.eye(self.d)
A[-1, -1] = 0.
self.P = np.dot(np.linalg.inv(Q), A * self.lengths[None, :]) / 2.
self.U = np.eye(self.d) - np.eye(self.d, k=-1)
self.U = self.U[:, :-1]
self.G = np.dot(self.P.T * self.masses[None, :], self.P)
# incidator variables for angles in a state representation
self.angles = np.zeros(2 + self.d * 2 + 1, dtype=np.bool)
self.angles[2:2 + self.d - 1] = True
self.angles[-self.d - 2:] = True
self.actions = cartesian((d - 1) * [[-2., 0., 2]])
self.actions_num = len(self.actions)
self.statespace_limits = [[-15, 15]] * 2 + [[-np.pi, np.pi]] * (d - 1) \
+ [[-2, 2]] * 2 + [[-np.pi * 2, np.pi * 2]] * d
self.statespace_limits = np.array(self.statespace_limits)
self.continuous_dims = range(self.statespace_limits.shape[0])
super(Swimmer, self).__init__()
