Agentic Reinforcement Learning

Agentic Reinforcement Learning (Agentic RL) extends reinforcement learning optimization from single-turn text completions to multi-step environment trajectories. It optimizes an agent's planning, tool selection, and recovery policies directly against verifiable task success rates, step efficiency, and interactive environment rewards.