The Rise and Potential of Large Language Model Based Agents: A Survey

Reference: Xi, Chen, Guo, He, Ding, Hong, Zhang, Wang, Jin, Zhou, Zheng, Fan, Wang, Xiong, Zhou, Wang, Jiang, Zou, Liu, Yin, Dou, Weng, Cheng, Zhang, Qin, Zheng, Qiu, Huang, Gui (2023). Fudan NLP Group, arXiv preprint. Source file: 2309.07864.pdf. URL

Summary

A comprehensive survey of LLM-based agents organised around a three-component conceptual framework — brain, perception, action — that the authors propose as a general template for agent construction. The brain covers natural-language interaction, knowledge, memory, reasoning/planning, and transferability; perception covers textual, visual, auditory, and other inputs; action covers textual output, tool use, and embodied action.

The survey then examines agents in practice (single-agent task/innovation/lifecycle deployments; multi-agent cooperative and adversarial interaction; human-agent instructor-executor and equal-partnership paradigms) and agent societies (personality, social behaviour, environments, society simulation, ethical/social risks). A final discussion chapter covers evaluation, adversarial robustness, trustworthiness, scaling the number of agents, and open problems — directly feeding the threat taxonomy of AI Agents Under Threat.

Key Ideas

• Brain/perception/action triad as a unifying architecture for LLM agents.
• Single-agent vs multi-agent vs human-agent deployment axes.
• Cooperative complementarity and adversarial advancement as the two poles of multi-agent interaction.
• Agent society simulation (à la Generative Agents) as both a scientific instrument and a risk surface.
• Dedicated treatment of adversarial robustness and trustworthiness as first-class concerns in agent design.

Connections

• LLM Agents
• Multi-Agent Systems
• AI Agents Under Threat
• Tool Use
• Agent Security
• Generative Agents

Conceptual Contribution

• Claim: LLM-based agents should be understood through a unified brain/perception/action framework, with deployments spanning single-agent, multi-agent, and human-agent configurations, and societies displaying emergent social phenomena that demand first-class security and trustworthiness analysis.
• Mechanism: Literature synthesis organised around the three-component architecture, three deployment paradigms, and an agent-society lens; taxonomy of cooperative vs adversarial multi-agent interaction; catalogue of open problems in robustness, trustworthiness, and scaling.
• Concepts introduced/used: brain/perception/action triad, instructor-executor vs equal-partnership paradigms, agent society, adversarial robustness, Tool Use, Multi-Agent Systems, LLM Agents.
• Stance: survey
• Relates to: The brain/perception/action decomposition directly informs the perception/brain/action threat axes used by AI Agents Under Threat; multi-agent cooperation analysis motivates ClawWorm Self-Propagating Attacks Across LLM Agent Ecosystems and the inter-agent risks catalogued in SoK The Attack Surface of Agentic AI.

Tags

#llm-agents #survey #foundational #multi-agent #agent-architecture