What is Reinforcement Learning? At the core of reinforcement learning is the concept that the optimal behavior or action is reinforced by a positive reward.

Interview with the creators of InstructGPT, one of the first major applications of reinforcement learning with human feedback (RLHF) to train large language models that influenced subsequent LLM ...

Reinforcement learning with human feedback is critical to not only ensuring the model’s alignment, it’s crucial to the long-term success and sustainability of generative AI as a whole.

Moving beyond the slow, costly trial-and-error of RL, GEPA teaches AI systems to learn and improve using natural language.

Reinforcement learning is a branch of machine learning concerned with using experience gained through interacting with the world and evaluative feedback to improve a system's ability to make ...

A Collins, L Thomas, Comparing reinforcement learning approaches for solving game theoretic models: a dynamic airline pricing game example, The Journal of the Operational Research Society, Vol. 63, No ...

For these problems, the hybrid AI was 63 percent faster at learning a solution compared to traditional reinforcement learning, decreasing its learning effort from 270 guesses to 100. Now that ...

Reinforcement Learning does NOT make the base model more intelligent and limits the world of the base model in exchange for early pass performances. Graphs show that after pass 1000 the reasoning ...