This survey examines the evolution of LLM-driven intelligent agents, proposing brain-inspired modular architectures that integrate cognitive science with computational research to achieve advanced reasoning and perception.
* **Modular Cognitive Frameworks:** Mapping human functions—such as memory, world modeling, goals, and emotion—onto structured AI modules.
* **Autonomous Self-Enhancement:** Enabling adaptive evolution through continuous learning and automated optimization in dynamic environments.
* **Collective Multi-Agent Systems:** Exploring emergent social dynamics and collective intelligence within collaborative agent networks.
* **Trustworthy & Secure Deployment:** Addressing the critical need for ethical alignment, robustness, and security to ensure safe real-world use.
* **Modular Cognitive Frameworks:** Mapping human functions—such as memory, world modeling, goals, and emotion—onto structured AI modules.
* **Autonomous Self-Enhancement:** Enabling adaptive evolution through continuous learning and automated optimization in dynamic environments.
* **Collective Multi-Agent Systems:** Exploring emergent social dynamics and collective intelligence within collaborative agent networks.
* **Trustworthy & Secure Deployment:** Addressing the critical need for ethical alignment, robustness, and security to ensure safe real-world use.
