Looking at a "potential photonic implementation," the authors developed a modified bandit Q-learning algorithm and validated its effectiveness through numerical simulations.

Examples of reinforcement learning algorithms include Monte Carlo, Q-learning, SARSA, Deep Q Network (DQN), and many others.

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

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 ...

We propose for risk-sensitive control of finite Markov chains a counterpart of the popular Q-learning algorithm for classical Markov decision processes. The algorithm is shown to converge with ...