
The evolving realm of artificial intelligence (AI) has encountered significant hurdles, especially concerning Long Language Model (LLM) agent stability when navigating intricate scenarios. One of the more pressing issues is the instability that arises during agent training with Reinforcement Learning (RL). This instability is largely attributed to the unpredictable feedback from complex environments and the requisite multi-step decision-making processes. These