Render the simulated state-action `trajectories` for Navigation domain.

        Args:
            stats: Performance statistics.
            trajectories: NonFluents, states, actions, interms and rewards.
            batch: Number of batches to render.

def render(self,
            trajectories: Tuple[NonFluents, Fluents, Fluents, Fluents, np.array],
            batch: Optional[int] = None) -> None:
        '''Render the simulated state-action `trajectories` for Navigation domain.

        Args:
            stats: Performance statistics.
            trajectories: NonFluents, states, actions, interms and rewards.
            batch: Number of batches to render.
        '''

        non_fluents, initial_state, states, actions, interms, rewards = trajectories

        non_fluents = dict(non_fluents)
        states  = dict((name, fluent[0]) for name, fluent in states)
        actions = dict((name, fluent[0]) for name, fluent in actions)
        rewards = rewards[0]

        idx = self._compiler.rddl.domain.state_fluent_ordering.index('location/1')

        start = initial_state[idx][0]
        g = non_fluents['GOAL/1']
        path = states['location/1']
        deltas = actions['move/1']

        centers = non_fluents['DECELERATION_ZONE_CENTER/2']
        decays = non_fluents['DECELERATION_ZONE_DECAY/1']
        zones = [(x, y, d) for (x, y), d in zip(centers, decays)]

        self._ax1 = plt.gca()

        self._render_state_space()
        self._render_start_and_goal_positions(start, g)
        self._render_deceleration_zones(zones)
        self._render_state_action_trajectory(start, path, deltas)

        plt.title('Navigation', fontweight='bold')
        plt.legend(loc='lower right')
        plt.show()