An overview of our research on agentic RL. In this work, we systematically investigate three dimensions of agentic RL: data, algorithms, and reasoning modes. Our findings reveal: Real end-to-end ...

PRIME-RL is a framework for large-scale asynchronous reinforcement learning. It is designed to be easy-to-use and hackable, yet capable of scaling to 1000+ GPUs. Beyond that, here is why we think you ...

Abstract: Reinforcement learning (RL) algorithms have been successfully applied to control tasks associated with unmanned aerial vehicles and robotics. In recent years, safe RL has been proposed to ...

Abstract: Synchronized and fresh communication of common information is vitally important in numerous multi-user network scenarios, whereby end-users must perform coordinated real-time action with the ...

Large-ticket recreational purchases have long been hampered by fragmented financing processes that leave both dealers and consumers frustrated with slow decisions and limited credit options. While ...