Graphs Meet AI Agents: Taxonomy, Progress, and Future Opportunities
This survey presents a first systematic review of how graphs can empower AI agents. It Focuses on the potential of graph learning to bolster agent planning, agent execution, agent memory, and multiagent coordination. Explores the reciprocal relationship, detailing how AI agents can, in turn, empower and refine graph learning processes. Outlines promising applications and identify key future research opportunities Preliminaries AI Agents: An AI agent is an intelligent model capable of perceiving its environment and making autonomous decisions to achieve specific goals. ...