Baldassarre Gianluca, Nolfi Stefano, Parisi Domenico
Institute of Cognitive Sciences and Technologies, National Research Council (ISTC-CNR), 15 Viale Marx, 00137 Rome, Italy.
Artif Life. 2003 Summer;9(3):255-67. doi: 10.1162/106454603322392460.
We present a set of experiments in which simulated robots are evolved for the ability to aggregate and move together toward a light target. By developing and using quantitative indexes that capture the structural properties of the emerged formations, we show that evolved individuals display interesting behavioral patterns in which groups of robots act as a single unit. Moreover, evolved groups of robots with identical controllers display primitive forms of situated specialization and play different behavioral functions within the group according to the circumstances. Overall, the results presented in the article demonstrate that evolutionary techniques, by exploiting the self-organizing behavioral properties that emerge from the interactions between the robots and between the robots and the environment, are a powerful method for synthesizing collective behavior.
我们展示了一组实验,其中模拟机器人通过进化获得聚集并一起朝着光源目标移动的能力。通过开发和使用能够捕捉所形成结构特性的定量指标,我们表明进化后的个体展现出有趣的行为模式,即机器人组作为一个整体行动。此外,具有相同控制器的进化后的机器人组表现出原始形式的情境专业化,并根据具体情况在组内发挥不同的行为功能。总体而言,本文所呈现的结果表明,进化技术通过利用机器人之间以及机器人与环境之间相互作用所产生的自组织行为特性,是合成集体行为的一种强大方法。