An AI agent is an entity in artificial intelligence that perceives its environment through sensors, processes information, and takes actions to achieve specific goals or objectives.
It operates autonomously or semi-autonomously and is designed to make decisions based on inputs, learned experiences, or pre-programmed rules.
Key Components of an AI Agent:
1. Perception: The agent gathers information from its environment using sensors (e.g., cameras, microphones, or digital data feeds).
2. Processing: It interprets the input, reasons about the situation, and makes decisions using algorithms, machine learning models, or heuristics.
3. Action: The agent takes actions to influence its environment, such as moving, generating outputs, or making recommendations.
4. Learning: Many AI agents can adapt over time by learning from data, feedback, or experience.
Types of AI Agents:
1. Reactive Agents: These operate based on the current state of the environment, without memory or foresight. (e.g., a thermostat adjusting temperature).
2. Deliberative Agents: These use planning and reasoning to make decisions based on both current and future states (e.g., self-driving cars).
3. Learning Agents: These improve their performance over time by learning from their experiences (e.g., recommendation systems).
4. Multi-Agent Systems: Groups of AI agents that interact to solve problems collaboratively or competitively (e.g., swarm robotics).
Examples:
• A chatbot assisting customers online.
• A virtual assistant like Siri or Alexa.
• Autonomous robots or vehicles.
• Recommendation systems on streaming platforms or e-commerce sites.
AI agents can range from simple rule-based systems to highly sophisticated models using advanced machine learning and deep learning techniques.