AI agents are autonomous programs that perceive their environment and take actions to achieve specific goals.
They can be classified as simple reflex agents, model-based agents, goal-based agents, and utility-based agents.
Some AI agents learn from experience using machine learning algorithms, improving their performance over time.
They are used in virtual assistants, self-driving cars, recommendation systems, and healthcare diagnostics.
AI agents interact with dynamic or static environments using sensors and actuators.
Multiple AI agents can collaborate or compete, forming multi-agent systems to solve complex tasks.
The use of AI agents raises ethical concerns, including privacy, bias, and decision accountability.
They operate autonomously and adapt to changes in their environment to achieve their objectives.
Building AI agents involves challenges like ensuring security, robustness, and interpretability.
They are expected to revolutionize industries by enhancing automation and decision-making processes.