A survey on large language model based autonomous agents

🤖 Plain-English Summary

Abstract Autonomous agents have long been a research focus in academic and industry communities. Finally, we delve into the evaluation strategies commonly used for LLM-based autonomous agents.

🔑 Key Findings

• Previous research often focuses on training agents with limited knowledge within isolated environments, which diverges significantly from human learning processes, and makes the agents hard to achieve human-like decisions.
• Recently, through the acquisition of vast amounts of Web knowledge, large language models (LLMs) have shown potential in human-level intelligence, leading to a surge in research on LLM-based autonomous agents.
• In this paper, we present a comprehensive survey of these studies, delivering a systematic review of LLM-based autonomous agents from a holistic perspective.

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