When someone starts a new job, early training may involve shadowing a more experienced worker and observing what they do ...

Multiagent reinforcement learning (MARL) has received increasing attention and been used to solve cooperative multiagent decision-making and learning control tasks. However, the high complexity of the ...

During the summer, kids can forget some of what they learned during the school year. They recover quickly, but here are some ...

ChatGPT is surprisingly good at piloting spacecraft, according to a team that trained it to participate in a simulated ...

Binunya, F. and Zhou, H. (2025) Multilingual Text Recognition and Assistance for Low-Resource Languages Using Computer Vision. Open Access Library Journal, 12, 1-20. doi: 10.4236/oalib.1113574 .

In smart grid management, ML enables dynamic control of distributed energy sources, managing real-time energy flows and ...

A Scenario-Based AI Simulation Coach with Integrated Feedback and Reinforcement for Difficult Conversations ...

A new machine learning approach tries to better emulate the human brain, in hopes of creating more capable agentic AI.

The examples are nothing if not relatable: preparing breakfast, or playing a game of chess or tic-tac-toe. Yet the idea of learning from the environment and taking steps that progress toward a goal ...

A more recent example is the use of reinforcement learning to make chatbots such as ChatGPT more helpful. Reinforcement learning is also being used to improve the reasoning capabilities of chatbots.

OpenAI’s reinforcement fine-tuning (RFT) is set to transform how artificial intelligence (AI) models are customized for specialized tasks. Using reinforcement learning, this method improves a ...

OpenAI introduced Reinforcement Fine-Tuning (RFT), a novel AI customization method that emphasizes reasoning over rote learning, allowing models to handle domain-specific tasks with precision.