Summary
In this chapter, you learned how to restructure a genetic algorithm into a client-server model. The client uses asynchronous I/O, while the server, built with Flask, handles fitness function calculations. The server component was then successfully deployed to the cloud using Zappa, making it operational as an AWS Lambda service. This approach demonstrates the effective use of serverless computing in enhancing the performance of genetic algorithms.
In the next chapter, we’ll explore how genetic algorithms can be creatively applied in the art world. Specifically, we’ll learn how these algorithms can be used to reconstruct images of famous paintings using semi-transparent, overlapping shapes. This approach not only offers a unique blend of art and technology but also provides an insightful look into the versatile applications of genetic algorithms in fields beyond traditional computing.
