A Gradient Descent Inspired Approach to Optimization of Physics Question

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.