评分 6 · 来源：cs.AI updates on arXiv.org · 发布于 2026-04-17
评分依据：Systematic framework for measuring exploration vs exploitation in LM agents, relevant to agentic AI design but fairly theoretical
arXiv:2604.13151v1 Announce Type: new Abstract: Language Model (LM) agents are increasingly used in complex open-ended decision-making tasks, from AI coding to physical AI. A core requirement in these settings is the ability to both explore the problem space and exploit acquired knowledge effectively. However, systematically distinguishing and quantifying exploration and exploitation from observed actions without access to the agent’s internal policy remains challenging. To address this, we design controllable environments inspired by practical embodied AI scenarios.