def agent_reward()

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

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

    def agent_reward(self, agent, world):
        # Agents rewarded if Bob can reconstruct message, but adversary (Eve) cannot
        good_listeners = self.good_listeners(world)
        adversaries = self.adversaries(world)
        good_rew = 0
        adv_rew = 0
        for a in good_listeners:
            if (a.state.c == np.zeros(world.dim_c)).all():
                continue
            else:
                good_rew -= np.sum(np.square(a.state.c - agent.goal_a.color))
        for a in adversaries:
            if (a.state.c == np.zeros(world.dim_c)).all():
                continue
            else:
                adv_l1 = np.sum(np.square(a.state.c - agent.goal_a.color))
                adv_rew += adv_l1
        return adv_rew + good_rew