限られたセンシング能力を持つ進化する群れにおける環境誘発型の集団行動の創発
Environment induced emergence of collective behaviour in evolving swarms with limited sensing
限られたセンシング・通信能力しか持たないロボット群が環境特徴の勾配を追従する課題に対し、差分進化でニューラルネットワーク制御器を進化させ、環境条件や群れサイズを変えて柔軟性とスケーラビリティを評価した研究。
著者: Fuda van Diggelen, Jie Luo, Tugay Alperen Karagüzel, Nicolas Cambier, Eliseo Ferrante, A. E. Eiben
分類: cs.RO, cs.AI
原文アブストラクト
Designing controllers for robot swarms is challenging, because human developers have typically no good understanding of the link between the details of a controller that governs individual robots and the swarm behavior that is an indirect result of the interactions between swarm members and the environment. In this paper we investigate whether an evolutionary approach can mitigate this problem. We consider a very challenging task where robots with limited sensing and communication abilities must follow the gradient of an environmental feature and use Differential Evolution to evolve a neural network controller for simulated robots. We conduct a systematic study to measure the flexibility and scalability of the method by varying the size of the arena and number of robots in the swarm. The experiments confirm the feasibility of our approach, the evolved robot controllers induced swarm behavior that solved the task. We found that solutions evolved under the harshest conditions (where the environmental clues were the weakest) were the most flexible and that there is a sweet spot regarding the swarm size. Furthermore, we observed collective motion of the swarm, showcasing truly emergent behavior that was not represented in- and selected for during evolution.
