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Evolutionary Developmental Soft Robotics As a Framework to Study Intelligence and Adaptive Behavior in Animals and Plants

机译:进化发展软机器人作为研究动植物智能和适应行为的框架

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In this paper a comprehensive methodology and simulation framework will be reviewed, designed in order to study the emergence of adaptive and intelligent behavior in generic soft-bodied creatures. By incorporating artificial evolutionary and developmental processes, the system allows to evolve complete creatures (brain, body, developmental properties, sensory and control system, etc.) for different task environments. Whether the evolved creatures will resemble animals or plants is in general not known a priori, and depends on the specific task environment set up by the experimenter. In this regard, the system may offer a unique opportunity to explore differences and similarities between these two worlds. Different material properties can be simulated and optimized, from a continuum of soft/stiff materials, to the interconnection of heterogeneous structures, both found in animals and plants alike. The adopted genetic encoding and simulation environment are particularly suitable in order to evolve distributed sensory and control systems, which play a particularly important role in plants. After a general description of the system some case studies will be presented, focusing on the emergent properties of the evolved creatures. Particular emphasis will be on some unifying concepts that are thought to play an important role in the emergence of intelligent and adaptive behavior across both the animal and plant kingdoms, such as morphological computation and morphological developmental plasticity. Overall, with this paper we hope to draw attention on set of tools, methodologies, ideas and results which may be relevant to researchers interested in plant-inspired robotics and intelligence.
机译:在本文中,将对综合的方法论和仿真框架进行审查,以研究通用软体动物中适应性和智能行为的出现。通过结合人工的进化和发育过程,该系统允许为不同的任务环境进化完整的生物(大脑,身体,发育特性,感觉和控制系统等)。通常,先天不知道进化的生物会像动物还是植物,这取决于实验者建立的特定任务环境。在这方面,该系统可以提供探索这两个世界之间异同的独特机会。从连续的软/硬材料到动物和植物中都可以发现的异质结构的相互连接,可以模拟和优化不同的材料特性。所采用的遗传编码和模拟环境特别适合于发展分布式感官和控制系统,这些系统在植物中起着特别重要的作用。在对系统进行一般描述之后,将提出一些案例研究,重点放在进化生物的新兴特性上。将特别强调一些统一的概念,这些概念被认为在动植物界的智能和适应行为的出现中起着重要作用,例如形态计算和形态发育可塑性。总体而言,我们希望通过本文吸引对与植物启发式机器人和智能技术感兴趣的研究人员相关的工具,方法论,思想和结果的关注。

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