

In the next part, a brief introduction to GA will be demonstrated as well as its application in training a neural network that can play Flappy Bird game. In other words, many people consider it as a complete black box. As for many other metaheuristic methods, controversial reviews have been made around GA due to the lack of core and concrete mathematical foundation. GA is an artificial intelligence metaheuristic search technique that is derived from the Darwin’s theory of biological organism evolution. Simulated annealing, ant colony, bee swarm, harmony search are examples of algorithm that are derived from different fields rather than computer science. Metaheuristics algorithm use metaphors, usually come from unrelated field to define selection algorithm. Mathematical programming algorithms have the most rigorous foundations, and it may be possible to prove that the algorithm actually converges, check that the proposed solution is close to at least a local optimum, and to estimate the rate of convergence. Optimization algorithms can roughly be divided into three classes: mathematical programming algorithms, heuristics, and metaheuristics. For example, the design of analog circuits \(^\) and optimization of space-born antennae \(^\) are developed using GA. GA (Genetic Algorithm) has been successful in complex engineering applications that involved multiple objective, non well-defined optimization function. An implementation of GA on building an AI for a famous arcade game namely Flappy Bird is provided. This report demonstrate how GA approaches to a optimization problem in general. Genetic algorithm is a heuristic search technique in artificial intelligent to find the most optimized solution for a given problem based on crossover, mutation, selection and some other techniques inspired by Darwin’s theory of evolution. Machine are becoming more and more efficient, many applications have been made recently to solve complex problem. In today’s world, an intelligent and optimal problem solving approaches are required in every field. MarI/O is a great example of unbeatable AI for game achieved by Neural Network model and Evolutionary Algorithm (Neat).
#Easy flappy bird online code
Source Code in Python for the implementation of AI for Flappy Bird game will be provided, the external package I use in my implementation is only Numpy to make use of matrix form.Īfter reading this blog, you will be able to build AI for a lot of simple games, not just FlappyBird.

The first thing we’ll need to do is create all the sprites and the backdrop we need for the game. If the bird touches an obstacle or the ground, the game will end.The player will press the spacebar to make the bird fly.When the player clicks on the start button the game will begin.When the green flag is pressed a start button will appear.By the end of the project, you will be able to use these concepts to create a simple game. This project focuses on using knowledge of Scratch components like if-statements and operators. These will be the core concepts used and built upon in this project. Before beginning, you should already have some experience with creating costumes, variables, and if statements, and using operators. This is a beginner-level project for those who are new to Scratch.
