AI Agents: Progress, Architecture, and Applications

Dear Colleagues,

Artificial intelligence agents are rapidly transforming how intelligent systems perceive, reason, and act in the world. Driven by advances in large language models (LLMs), multi-agent frameworks, and retrieval-augmented generation, AI agents are now capable of executing complex, multi-step tasks across diverse and dynamic environments with minimal human supervision.

This Topic aims to consolidate cutting-edge research on AI agents, spanning theoretical foundations, architectural innovations, and practical deployments across domains. We invite contributions exploring agent architectures—including LLM-based, multi-agent, and fully autonomous systems—as well as advances in planning, reasoning, decision-making, tool use, and memory mechanisms. Equally, we welcome studies on the application of AI agents in healthcare, education, robotics, and industry, alongside work addressing safety, alignment, and the evaluation of agentic systems. Research on human–agent collaboration and interaction is also of great interest.

Submissions are welcome on topics including, but not limited to: agent architectures (LLM-based, multi-agent systems, autonomous agents); planning, reasoning, and decision-making in AI agents; tool use, memory, and retrieval-augmented generation; AI agents in healthcare, education, robotics, and industry; safety, alignment, and evaluation of agentic systems; and human–agent interaction and collaboration.

We welcome original research articles, review papers, and short communications addressing any of these themes. Interdisciplinary contributions that bridge AI, cognitive science, systems engineering, and domain-specific applications are especially encouraged.

Prof. Dr. Christophe Cruz
Prof. Dr. Hocine Cherifi
Dr. Maria Alice Bertolim Nicoleau
Topic Editors