AI agents and expert systems are both forms of artificial intelligence, but they serve different purposes and operate in distinct ways. An AI agent is a software entity designed to perform tasks autonomously or semi-autonomously. It can perceive its environment, make decisions, and act based on its programming and the data it receives. AI agents are often used in applications like virtual assistants, chatbots, and automated trading systems, where they interact dynamically with users or environments.
On the other hand, expert systems are specialized software designed to mimic the decision-making ability of a human expert in a specific domain. They use a collection of rules or a knowledge base to provide solutions or recommendations based on input data. For instance, a medical diagnosis expert system may analyze symptoms and medical history to suggest possible conditions, relying on a structured set of rules provided by medical professionals. Unlike AI agents, which can learn and adapt over time, expert systems mainly operate under predefined rules and do not learn from new data unless explicitly updated.
In summary, the primary difference lies in their design and functionality. AI agents are generally more flexible and capable of adapting to new information in real-time, while expert systems follow a rigid set of rules to provide expert-level advice. Developers choose between the two based on the requirements of their projects, whether they need dynamic systems that can learn and evolve or stable systems that rely on established knowledge.