{"title":"A Gradient Descent Inspired Approach to Optimization of Physics Question","authors":"Feihong Liu, Yu Sun","doi":"10.5121/csit.2022.121708","DOIUrl":null,"url":null,"abstract":"Many people believe that the crouch start was the best way to start a sprint [1]. While it seems intuitive, when the process of running is dissected using specific physical and mathematical representations, the question of “what is the best starting position” becomes harder to answer [2]. This paper aims to examine this phenomenon through a computer science approach inspired by gradient descent. Specifically, this paper aims to maximise the distance covered by a runner in ten steps. Assuming that runners do their best on every step and that their motion is not slowed by friction or air resistance, we will generate a hypothetical environment to study what the best strategy is for reaching the furthest distance within ten steps.","PeriodicalId":170432,"journal":{"name":"Signal & Image Processing Trends","volume":"100 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Signal & Image Processing Trends","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5121/csit.2022.121708","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Many people believe that the crouch start was the best way to start a sprint [1]. While it seems intuitive, when the process of running is dissected using specific physical and mathematical representations, the question of “what is the best starting position” becomes harder to answer [2]. This paper aims to examine this phenomenon through a computer science approach inspired by gradient descent. Specifically, this paper aims to maximise the distance covered by a runner in ten steps. Assuming that runners do their best on every step and that their motion is not slowed by friction or air resistance, we will generate a hypothetical environment to study what the best strategy is for reaching the furthest distance within ten steps.