def benchmark_data()

in multiagent/scenarios/simple_spread.py [0:0]

• 17 lines of code
• 7 McCabe index (conditional complexity)

    def benchmark_data(self, agent, world):
        rew = 0
        collisions = 0
        occupied_landmarks = 0
        min_dists = 0
        for l in world.landmarks:
            dists = [np.sqrt(np.sum(np.square(a.state.p_pos - l.state.p_pos))) for a in world.agents]
            min_dists += min(dists)
            rew -= min(dists)
            if min(dists) < 0.1:
                occupied_landmarks += 1
        if agent.collide:
            for a in world.agents:
                if self.is_collision(a, agent):
                    rew -= 1
                    collisions += 1
        return (rew, collisions, min_dists, occupied_landmarks)