Computing pioneer Alan Turing suggested training machines with rewards and punishments. Two computer scientists put the idea into practice in the 1980s and set the stage for the likes of ChatGPT.

Examples of Reinforcement Learning: High computational cost ... Data inefficiency: RL algorithms often require a large number of interactions with the environment to learn effectively.

Researchers from UCLA and Meta AI have introduced d1, a novel framework using reinforcement learning (RL) to significantly enhance the reasoning capabilities of diffusion-based large language models ...

Reinforcement learning (RL ... feedback based on its relevance to the RL agent's learning objectives. Auto-classification uses algorithms to automatically assign categories, labels or tags ...

Researchers from Nanjing University and Carnegie Mellon University have introduced an AI approach that improves how machines learn from past data—a process known as offline reinforcement learning.

A more recent example is the use of reinforcement ... Researchers have used specific algorithms developed in reinforcement learning to explain experimental findings in people and animals' dopamine ...