AI Agents: Architecture, Reasoning, Applications and Emerging Challenges

There have been rapid advancements in the field of Artificial Intelligence (AI) wherein the technology has come a long way from its rudimentary form, which comprised of rule-based systems and algorithms for specific purposes to becoming very advanced and being able to understand natural languages, create content, make sense of the information and interact with the computerized world around it. One of the many advancements that have occurred in this domain is that of artificial intelligence agents. Artificial intelligence agents are a step ahead in the evolution of traditional AI systems in the sense that it enables the AI system to achieve some specific goals on its own. In this paper, the comprehensive conceptual study of the AI agent is carried out. The architecture, the main characteristics, the reasons, uses, benefits, problems and potential of the agent are analyzed. In addition, the paper covers the topic of the utilization of large language models as reasoners of the agent-based system and the necessity of orchestration, memory, external tools, planning and feedback in it. The Chain-of-Thought, ReAct, and Tree-of-Thought reasoning methods are also considered in the context of task execution by an autonomous agent. Besides, in this paper, the applications of AI agents in such spheres as education, healthcare, business, software development, research and travel services are described. Even though there are great opportunities of using AI agents in various fields, there are some difficulties like hallucination, safety, privacy, prompt injection, memory manipulation, too much autonomy and liability. For that reason, the further development of AI agents should concentrate not only on increasing autonomy of agents but also on making them reliable, safe, transparent and controllable.