The Data Science Doctor explains how to use the reinforcement learning branch of machine learning with the Q-learning approach, providing code on how to solve a maze problem for an easy-to-understand ...

Introduction What is Q-learning? Q-learning is a type of reinforcement learning algorithm that teaches agents how to act in a given environment to maximise rewards over time.

Unlike basic Q-learning algorithms, which generally focus on finding the optimal path to maximize rewards, the modified bandit Q-learning algorithm aims to learn the optimal Q value for every ...

We demonstrate that the deep Q-network agent, receiving only the pixels and the game score as inputs, was able to surpass the performance of all previous algorithms and achieve a level comparable ...

The battle at OpenAI was possibly due to a massive breakthrough dubbed Q* (Q-learning). Q* is a precursor to AGI. What Q* might have done is bridged a big gap between Q-learning and pre-determined ...