面向大语言模型的智能体环境工程：环境建模、合成、评估与应用综述

摘要

环境作为基于大语言模型（LLM）的智能体在不同场景中的交互系统，在推动模型能力持续演进中发挥着关键作用。尽管其重要性不言而喻，但现有工作缺乏系统性的分类与深入分析。本文从环境工程生命周期的视角系统梳理了当前有关智能体环境的研究，涵盖其建模、合成、评估与应用四个维度。具体而言：首先，从八个属性与八个领域的角度介绍代表性环境，详细分析其发展路径并揭示核心能力；其次，针对自动化环境合成，引入符号合成与神经合成两种范式，并展示各范式下的不同评估方法；再次，从智能体-环境协同演化的视角探讨相应环境应用，重点从记忆驱动的经验演化、编排驱动的工作流演化、轨迹驱动的离线演化及探索驱动的在线演化四个互补维度刻画动态环境中智能体演化的主要路径，同时识别出环境演化的三种范式——神经驱动型、难度驱动型与规模驱动型；最后，讨论若干有前景的未来方向，包括环境即服务、多智能体环境及神经符号环境。

English

Environments serve as interactive systems for large language model (LLM) based agents across diverse scenarios and play a crucial role in driving the continual evolution of model capabilities. Despite this importance, existing work lacks a systematic categorization and deep analysis. This paper systematically studies current researches on agentic environments from the perspective of the environment engineering lifecycle, covering their modeling, synthesis, evaluation and application. Specifically, the paper first introduces representative environments from the perspectives of eight attributes and eight domains, providing detailed analyses of their development paths and highlighting their core capabilities. Second, for automated environment synthesis, two paradigms are introduced, such as symbolic synthesis and neural synthesis. This paper also shows different environment evaluation methods in each paradigm. Thirdly, the corresponding environment applications from the perspective of agent-environment co-evolution are discussed. In specific, the paper characterizes the primary pathways for agent evolution in dynamic environments from four complementary perspectives: memory-centric experience evolution, orchestration-centric workflow evolution, trajectory-centric offline evolution, and exploration-centric online evolution. And three paradigms of environment evolution are identified, namely neural-driven, difficulty-driven, and scaling-driven approaches. At last, several promising future directions are discussed, including Environment-as-a-Service, Multi-agent Environments, and Neural-Symbolic Environments.