def observation()

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

• 17 lines of code
• 7 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:  # world.entities:
            entity_pos.append(entity.state.p_pos - agent.state.p_pos)
        # entity colors
        entity_color = []
        for entity in world.landmarks:  # world.entities:
            entity_color.append(entity.color)
        # communication of all other agents
        comm = []
        other_pos = []
        for other in world.agents:
            if other is agent: continue
            comm.append(other.state.c)
            other_pos.append(other.state.p_pos - agent.state.p_pos)
        if not agent.adversary:
            return np.concatenate([agent.state.p_vel] + [agent.goal_a.state.p_pos - agent.state.p_pos] + [agent.color] + entity_pos + entity_color + other_pos)
        else:
            #other_pos = list(reversed(other_pos)) if random.uniform(0,1) > 0.5 else other_pos  # randomize position of other agents in adversary network
            return np.concatenate([agent.state.p_vel] + entity_pos + other_pos)