Hands-On Neuroevolution with Python

Agent position update

The position of the maze-solver agent within a maze needs to be updated in each simulation step after receiving the corresponding control signals from the controller ANN. The following code is executed to update the position of the maze-solver agent:

    def update(self, control_signals):        if self.exit_found:            return True # Maze exit already found        self.apply_control_signals(control_signals)        vx = math.cos(geometry.deg_to_rad(self.agent.heading)) * \                      self.agent.speed        vy = math.sin(geometry.deg_to_rad(self.agent.heading)) * \                      self.agent.speed        self.agent.heading += self.agent.angular_vel        if self.agent.heading > 360:            self.agent.heading -= 360        elif self.agent.heading < 0:            self.agent.heading += 360        new_loc = geometry.Point( x = ...