论文标题
机器人的在线改编作为生物开发提供表型可塑性
Online adaptation in robots as biological development provides phenotypic plasticity
论文作者
论文摘要
通过适当的动作对环境刺激做出反应的能力是所有生物体共有的特性，并且在机器人系统的设计中也寻求。表型可塑性为实现该特性提供了一种方法，因为它表征了那些从一种基因型可以反应不同环境的生物，而无需涉及遗传修饰。在这项工作中，我们研究了配备在线传感器适应的机器人中的表型可塑性。我们表明，布尔网络控制的机器人可以通过在不改变其结构的情况下调整接近传感器及其控制网络之间的耦合，从而通过避免碰撞来实现导航。换句话说，这些机器人以一种基因型（即网络）为特征，可以表达许多适合特定环境的表型。我们还表明，使得获得最佳总体表现成为可能的动态制度是至关重要的，这进一步证明了自然和人工系统能够最佳地平衡鲁棒性和适应性。
The ability of responding to environmental stimuli with appropriate actions is a property shared by all living organisms, and it is also sought in the design of robotic systems. Phenotypic plasticity provides a way for achieving this property as it characterises those organisms that, from one genotype, can express different phenotypes in response to different environments, without involving genetic modifications. In this work we study phenotypic plasticity in robots that are equipped with online sensor adaptation. We show that Boolean network controlled robots can attain navigation with collision avoidance by adapting the coupling between proximity sensors and their controlling network without changing its structure. In other terms, these robots, while being characterised by one genotype (i.e. the network) can express a phenotype among many that is suited for the specific environment. We also show that the dynamical regime that makes it possible to attain the best overall performance is the critical one, bringing further evidence to the hypothesis that natural and artificial systems capable of optimally balancing robustness and adaptivity are critical.
