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 ...

Transfer Learning for Reinforcement Learning Domains: A Survey Transfer Learning for Reinforcement Learning Domains: A Survey. Matthew E. Taylor and Peter Stone. Journal of Machine Learning Research, ...

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 ...

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

python library reinforcement-learning constraint-programming job-shop combinatorial-optimization job-shop-scheduling-problem graph-neural-networks reinforcement-learning-environments ...

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 ...

CleanRL is a Deep Reinforcement Learning library that provides high-quality single-file implementation with research-friendly features. The implementation is clean and simple, yet we can scale it to ...