The rStar2-Agent framework boosts a 14B model to outperform a 671B giant, offering a path to state-of-the-art AI without ...

A U.S. Naval Research Laboratory (NRL) research team successfully conducted the first reinforcement learning (RL) control of ...

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 adapts ...

First, let's discuss the core elements of this development, with algorithms being the most critical. In AI agent development, we often mention the use of machine learning algorithms, and of course, ...

This is largely due to the fact that current LLMs often struggle with complex code, multi-step logic, and abstract tasks, frequently exhibiting logical leaps, disorganized steps, and irrelevant ...

Reinforcement learning is one of the exciting branches of artificial intelligence. It plays an important role in game-playing AI systems, modern robots, chip-design systems, and other applications.

MILPITAS, Calif.--(BUSINESS WIRE)--Bigfoot Biomedical (Bigfoot), a leader in developing intelligent connected injection support systems, today announced the acquisition of a reinforcement learning ...

Scientists at UCL, Google DeepMind and Intrinsic have developed a powerful new AI algorithm that enables large sets of ...