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Agentic Environment Engineering for Large Language Models: A Survey of Environment Modeling, Synthesis, Evaluation, and Application

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agentic-environment-engineering-for-large-language-models-a-survey-of-environment-modeling-synthesis-evaluation-and-application-6d1c7833

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Aliases: Agentic Environment Engineering for Large Language Models: A Survey of Environment Modeling, Synthesis, Evaluation, and Application

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5arXiv · cs.CL·6d ago·source ↗

Survey: Agentic Environment Engineering for LLMs — Modeling, Synthesis, Evaluation, and Application

A comprehensive arXiv survey systematically reviews the design and engineering of interactive environments for LLM-based agents, covering the full lifecycle from environment modeling and synthesis to evaluation and application. The paper categorizes environments across eight attributes and eight domains, introduces symbolic and neural synthesis paradigms, and characterizes four pathways for agent-environment co-evolution including memory-centric, orchestration-centric, trajectory-centric, and exploration-centric approaches. It also identifies three paradigms of environment evolution (neural-driven, difficulty-driven, scaling-driven) and proposes future directions such as Environment-as-a-Service and multi-agent environments. This is a reference-organizing contribution for the rapidly growing agent tooling and evaluation space.

Evaluation and Benchmarking Agent and Tool Ecosystem Agentic Environment Engineering for Large Language Models: A Survey of Environment Modeling, Synthesis, Evaluation, and Application