MiniMax-M1 presents a flexible option for organizations looking to experiment with or scale up advanced AI capabilities while managing costs.

Reinforcement learning (RL) algorithms have performed well in playing challenging board and video games. More and more studies focus on improving the generalization ability of RL algorithms. The ...

The rapid evolution of Adaptive Education highlights the necessity of personalized learning paths that cater to the unique cognitive styles, preferences, and capabilities of each student. Traditional ...

Learning to code enhances students' problem-solving, logical thinking, and creativity across subjects, preparing them for future academic and career success. Integrating coding into education ...

"Unity RL Playground: A Versatile Reinforcement Learning Framework for Mobile Robots." arXiv preprint arXiv:2503.05146 (2025). PDF Ye, Linqi, Jiayi Li, Yi Cheng, Xianhao Wang, Bin Liang, and Yan Peng.

title = {Reinforcement Learning for Reasoning in Large Language Models with One Training Example}, author = {Wang, Yiping and Yang, Qing and Zeng, Zhiyuan and Ren, Liliang and Liu, Lucas and Peng, ...

Value function approximation plays an important role in reinforcement learning (RL) with continuous state space, which is widely used to build decision models in practice. Many traditional approaches ...