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Creating the 2D-Car-Simulation Readme File #2

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## 2D Car Simulation with Genetic Algorithms
### Description

Welcome to the exciting world of 2D car simulations powered by physics engines and genetic algorithms! 🎉 In this project, we'll explore how these powerful tools can be combined to create a virtual playground where cars evolve and adapt to their environment. Our simulation will take place in a highly realistic 2D world governed by the laws of physics, featuring mind-blowing elements like collision detection, contact callbacks, convex polygons and circles, multiple shapes per body, stable stacking, joints and constraints, and momentum and impulses, ensuring truly lifelike movements. Moreover, we'll implement our own physics engine, providing a deep understanding of the underlying mechanics and customization for our specific needs. Additionally, we'll harness the power of genetic algorithms (GAs) to create an intelligent and adaptive system that searches for the best car designs. GAs, inspired by natural selection and genetics, allow us to evolve solutions towards optimal performance. We'll start with a random initial population of car designs, evaluate their performance based on a fitness function (e.g., distance traveled, stability, etc.), and use genetic operations like crossover and mutation to create new generations. This iterative process continues until we find an optimal or satisfactory car design. By the end of this project, we will have a fully working simulation of 2D cars with all mentioned features and various parameters.

![Box2D](https://lh6.googleusercontent.com/proxy/1zq8zn9ujbz9enGGvaGx9ILhQV2wHluTr-wT5IBh4VccGGouqsFJ-oc_qo4VJjY8SsUzwzqh_90)

# References

[1] [Basics Of Genetic Algorithms](https://www.youtube.com/watch?v=XP2sFzp2Rig)

[2] [Understanding Genetic Algorithms](https://www.geeksforgeeks.org/genetic-algorithms/)

[3] [Physics Enginge](https://box2d.org/)


**Pre-requisites**: Basic Understanding of Web Development, Mechanics, Linear Algebra

**Difficulty**: Medium to Hard

**Mentors**: Manas Bavaskar, Sharan Poojari

**Domains**: Artificial Intelligence/Machine Learning, Computer Graphics and Simulation, Game Development