def observation()

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

• 55 lines of code
• 29 McCabe index (conditional complexity)

    def observation(self, agent, world):
        # get positions of all entities in this agent's reference frame
        entity_pos = []
        for entity in world.landmarks:
            if not entity.boundary:
                entity_pos.append(entity.state.p_pos - agent.state.p_pos)

        in_forest = [np.array([-1]), np.array([-1])]
        inf1 = False
        inf2 = False
        if self.is_collision(agent, world.forests[0]):
            in_forest[0] = np.array([1])
            inf1= True
        if self.is_collision(agent, world.forests[1]):
            in_forest[1] = np.array([1])
            inf2 = True

        food_pos = []
        for entity in world.food:
            if not entity.boundary:
                food_pos.append(entity.state.p_pos - agent.state.p_pos)
        # communication of all other agents
        comm = []
        other_pos = []
        other_vel = []
        for other in world.agents:
            if other is agent: continue
            comm.append(other.state.c)
            oth_f1 = self.is_collision(other, world.forests[0])
            oth_f2 = self.is_collision(other, world.forests[1])
            if (inf1 and oth_f1) or (inf2 and oth_f2) or (not inf1 and not oth_f1 and not inf2 and not oth_f2) or agent.leader:  #without forest vis
                other_pos.append(other.state.p_pos - agent.state.p_pos)
                if not other.adversary:
                    other_vel.append(other.state.p_vel)
            else:
                other_pos.append([0, 0])
                if not other.adversary:
                    other_vel.append([0, 0])

        # to tell the pred when the prey are in the forest
        prey_forest = []
        ga = self.good_agents(world)
        for a in ga:
            if any([self.is_collision(a, f) for f in world.forests]):
                prey_forest.append(np.array([1]))
            else:
                prey_forest.append(np.array([-1]))
        # to tell leader when pred are in forest
        prey_forest_lead = []
        for f in world.forests:
            if any([self.is_collision(a, f) for a in ga]):
                prey_forest_lead.append(np.array([1]))
            else:
                prey_forest_lead.append(np.array([-1]))

        comm = [world.agents[0].state.c]

        if agent.adversary and not agent.leader:
            return np.concatenate([agent.state.p_vel] + [agent.state.p_pos] + entity_pos + other_pos + other_vel + in_forest + comm)
        if agent.leader:
            return np.concatenate(
                [agent.state.p_vel] + [agent.state.p_pos] + entity_pos + other_pos + other_vel + in_forest + comm)
        else:
            return np.concatenate([agent.state.p_vel] + [agent.state.p_pos] + entity_pos + other_pos + in_forest + other_vel)