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 ...

A special category of algorithms, machine learning algorithms, try to “learn” based on a set of past decision-making examples.

We develop methodology for a multistage decision problem with flexible number of stages in which the rewards are survival times that are subject to censoring. We present a novel Q-learning algorithm ...