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人工智能算法的生物学视角:从进化论到遗传算法的课堂实践
作者姓名:和渊  武迪  袁中果  闫新霞
作者单位:中国人民大学附属中学 北京100080;中国人民大学附属中学信息技术教研组 北京100080;中国人民大学附属中学生物教研组 北京100080
基金项目:中国教育科学研究院中国STEM教育创新行动计划课题
摘    要:"人工智能+基于心智的生物学"课程的总体设计是从生物学视角来解释人工智能的算法逻辑,包括从生物学看终极算法、从计算机科学看认知神经科学、仿生人工智能、心智社会四大模块。"从进化论到遗传算法"是"从生物学看终极算法"模块的第3课时,该课时教学通过多足行走器等可视化算法内容培养学生对遗传算法的兴趣,通过类比达尔文的进化论使学生理解遗传算法的架构和逻辑、培养他们的跨学科思维能力,通过让学生模拟遗传算法的表演和上机实践过程进一步加深他们对遗传算法概念的理解、培养他们的信息意识和计算思维等。

关 键 词:人工智能  进化论  遗传算法

Biological Perspective of Artificial Intelligence Algorithm: Class Practice from Evolution Theory to Genetic Algorithm
Authors:HE Yuan  WU Di  YUAN Zhongguo  YAN Xinxia
Institution:(The High School Affiliated to Renmin University of China,Beijing 100083,China)
Abstract:The overall design of the course "Artificial Intelligence + Mentally Based Biology" is to explain the algorithmic logic of artificial intelligence from a biological perspective, including the master algorithm from biology, the cognitive neuroscience from computer science, bionic artificial intelligence, and mental society."From Evolution Theory to Genetic Algorithm" is the third lesson of the "Master Algorithm from Biology" module, which develops students interest in genetic algorithms through visual algorithm content such as multi-footed walkers, and teaches students, through the analogy of Darwin's theory of evolution, the structure and logic of genetic algorithms and interdisciplinary thinking;by allowing students to simulate the performance of genetic algorithms and the practice of the machine, to further deepen their understanding of the concept of genetic algorithms, and cultivate their information awareness and computational thinking.
Keywords:artificial intelligence  evolution theory  genetic algorithm
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