Evolutionary Theory in Artificial Intelligence:Genetic Algorithm Situational Teaching
During the learning process of artificial intelligence courses,students majoring in electronic information in applied undergraduate colleges often have weak mathematical foundations and limited knowledge of intelligence.In response to the above issues,this article proposes the use of situational teaching method to assist students in quickly mastering algorithm ideas,effectively improving the quality of course teach-ing,and provides a detailed description of genetic algorithm situational teaching cases.This article combines the characteristics of Suzhou Uni-versity of Science&Technology urban construction to design a pipeline inspection scenario,and demonstrates the genetic algorithm iteration process in simulating the snake shaped pipeline robot inspection process.In the process of interpreting the four important contents of genetic al-gorithm coding,selection,crossover,and mutation,the case organically incorporates ideological and political elements such as abstract sum-mary,optimized selection,cross integration,and the courage to innovate.This scenario teaching case has received good feedback in the appli-cation of graduate teaching in our school.In recent years,student grades and achievements have improved,and it has been promoted and ap-plied in other universities,providing a case reference for teaching design for frontline teachers.
artificial intelligencesituational teachinggenetic algorithmcurriculum ideology and politicssnake shaped pipeline robot
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