def goal_rewards()

in gym-compete/gym_compete/new_envs/multi_agent_env.py [0:0]

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

    def goal_rewards(self, infos=None, agent_dones=None):
        touchdowns = [self.agents[i].reached_goal()
                      for i in range(self.n_agents)]
        num_reached_goal = sum(touchdowns)
        goal_rews = [0. for _ in range(self.n_agents)]
        if num_reached_goal != 1:
            return goal_rews, num_reached_goal > 0
        for i in range(self.n_agents):
            if touchdowns[i]:
                goal_rews[i] = self.GOAL_REWARD
                if infos:
                    infos[i]['winner'] = True
            else:
                goal_rews[i] = - self.GOAL_REWARD
        return goal_rews, True