AIResearch
Mastering Agentic Techniques: AI Agent Reinforcement Learning
Reinforcement learning (RL) is key to aligning language models, from RLHF in AI assistants to newer RLVR workflows for reasoning and agent tasks, enabling more accurate domain-specific AI agents.
Reinforcement learning (RL) is central to aligning language models, from reinforcement learning with human feedback (RLHF) within AI assistants to newer reinforcement learning with verifiable rewards (RLVR) workflows for reasoning and agent tasks. RL is now becoming a practical technique for specialized AI where enterprises need more accurate agents for domain-specific workflows.