The development of every field relies on a few foundational classic books, and artificial intelligence is no exception.

This issue has now been addressed. Li Hang's newly launched book 'Machine Learning Methods (2nd Edition)' dedicates a chapter ...

Reinforcement learning focuses on rewarding desired AI actions and punishing undesired ones. Common RL algorithms include State-action-reward-state-action, Q-learning, and Deep-Q networks. RL ...

Deep reinforcement learning (DRL) is an exciting area of AI research, with potential applicability to a variety of problem areas. Some see DRL as a path to artificial general intelligence, or AGI ...

OpenAI leaked Q* so let’s dive into Q-Learning and how it relates to RLHF. Q-learning is a foundational concept in the field of artificial intelligence, particularly in the area of reinforcement ...

That OpenAI would try to use reinforcement learning to improve LLMs seems plausible because many of the company’s early projects, like video-game-playing bots, were centered on the technique.

Reinforcement learning (RL) is a type of machine learning where an agent learns to make decisions by interacting with an environment. Think of it like training a dog: every time the dog sits on ...

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 ...