− HEALTH Abstract Interest in the use of chatbots powered by large language models (LLMs) to support women and girls i…± LIFESTYLE Artificial Intelligence (AI) has moved beyond calculation and cognition into the domain of emotion and experi…+ SCIENCE Abstract Autonomous agents have long been a research focus in academic and industry communities. Previous res…+ HEALTH BACKGROUND: Artificial intelligence (AI), particularly generative AI, has emerged as a transformative tool in…± EDUCATION Medical education faces a scalability crisis, where rising class sizes strain individualized instruction, whi…± HEALTH BACKGROUND: The irrevocable alteration of medical education due to widespread access to large language models…− SCIENCE Online violence against women (OVAW) is a growing global problem with deepfakes in gender-based violence as o…+ CRIME This paper presents a systematic review of research (2020–2025) on the role of Large Language Models (LLMs) i…
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Science·G Space·Evidence-backed gain·Published 2026-07-20

A survey on large language model based autonomous agents

Abstract Autonomous agents have long been a research focus in academic and industry communities. 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 autono…

TRV-2026-0461Peer-reviewedPermanent record — cite & verify
A survey on large language model based autonomous agents

Layered path planning for an autonomous mobile robot by Haight, Timothy A.. Public domain

The quick read

Published March 22, 2024, this peer-reviewed survey examines the shift from agents trained with limited knowledge in isolated environments to agents built on large language models trained on vast Web knowledge. The authors propose a unified construction framework and systematically review applications and evaluation methods.

The work matters because it consolidates a fast-growing research area around LLM-based autonomy, highlighting potential for human-level intelligence while acknowledging prior limitations in achieving human-like decisions. What remains uncertain from the abstract alone is which specific applications have demonstrated robust real-world performance and what evaluation gaps persist.

Main points
  • Paper presents comprehensive survey of LLM-based autonomous agents from holistic perspective.
  • Authors propose unified framework for construction of LLM-based autonomous agents encompassing much previous work.
  • Survey covers evaluation strategies commonly used for LLM-based autonomous agents.
  • Abstract notes prior agents trained with limited knowledge in isolated environments diverge from human learning.
Gain

LLM-based autonomous agents leveraging vast Web knowledge show potential for human-level intelligence and enable applications across social science, natural science, and engineering.

The rundown

The survey organizes literature around how LLM-based agents are built, proposing a unified framework that encompasses much of previous work on autonomous agents.

It then reviews diverse applications in social science, natural science, and engineering, and summarizes evaluation strategies, ending with challenges and future directions for the field.

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