def decode_action(self, a_m, a_t, state, mode):
if mode == "max_probability":
a_m = np.argmax(a_m)
a_t = np.argmax(a_t)
elif mode == "sample":
#a_m += 0.01
a_m /= a_m.sum()
a_m = np.random.choice(range(3), p=a_m)
#a_t += 0.01
a_t /= a_t.sum()
a_t = np.random.choice(range(3), p=a_t)
action = Action()
if a_m == 0: # left
action.v_n = -1.0
elif a_m == 1: # ahead
action.v_t = +1.0
elif a_m == 2: # right
action.v_n = +1.0
if a_t == 0: # left
action.angular = +1.0
elif a_t == 1: # stay
action.angular = 0.0
elif a_t == 2: # right
action.angular = -1.0
if state.detect:
action.shoot = +1.0
else:
action.shoot = 0.0
return action
def select_action(self, state: RobotState):
action = Action()
pos = state.pos
vel = state.velocity
angle = state.angle
if state.detect:
action.shoot = +1.0
else:
action.shoot = 0.0
if ((pos[0]-self.target[0])**2 + (pos[1]-self.target[1])**2 < 0.1):
self.index = random.choice(self.connected[self.index])
self.target = self.avaiable_pos[self.index]
#print(self.target)
#self.index = (self.index + 1) % len(self.path)
#self.target = self.path[self.index]
v, omega = self.move.moveTo(pos, vel, angle, self.target)
action.v_t = v[0]
action.v_n = v[1]
action.omega = omega
return action