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Figure 7: Scenarios of LLM-based agent applications. We mainly introduce three scenarios: single-
agent deployment, multi-agent interaction, and human-agent interaction. A single agent possesses
diverse capabilities and can demonstrate outstanding task-solving performance in various application
orientations. When multiple agents interact, they can achieve advancement through cooperative or
adversarial interactions. Furthermore, in human-agent interactions, human feedback can enable
agents to perform tasks more efficiently and safely, while agents can also provide better service to
humans.

1. Assist users in breaking free from daily tasks and repetitive labor, thereby Alleviating human work

pressure and enhancing task-solving efficiency.

2. No longer necessitates users to provide explicit low-level instructions. Instead, the agent can

independently analyze, plan, and solve problems.
TheRiseandPotentialofLargeLanguageModel BasedAgents