In a previous post, we developed two AIs to play the game of Snake, of which, the first one implements a heuristic algorithm to select its moves while the second one consists of a deep neural network trained with a reinforcement learning algorithm (Deep Q-Learning). Afterward, in a second post, we used a genetic algorithm to create different generations of snakes where the best individuals … Continue reading AIs Battle Royale: The ultimate snake
Supervised learning, unsupervised learning and reinforcement learning are commonly recognized as the three main ways to train machine learning models. We can have a fourth one if we include the union of the first two, that is, semi-supervised learning. However, in this post we are going to introduce an alternative algorithm that can be used to both train and optimize neural network models: Genetic Algorithm. … Continue reading Teaching AI to play Snake with Genetic Algorithm
It is well known that two of the most fascinating fields of computer science are gaming and artificial intelligence. The gaming field saw its origins back in the 1970s when gaming consoles such as Atari 2600, along with graphics on computer screens and home computer games were introduced to the general public giving birth to different kinds of arcade games like Pong and Pacman. In … Continue reading Teaching AI to play Snake with Reinforcement Learning
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