AI Agents Explained: Theory, Applications, and Python Implementation

Author(s): A.Venkatesh

Originally published on Towards AI.

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Artificial Intelligence (AI) has revolutionized how we interact with technology. From chatbots to self-driving cars, AI is shaping the future. However, not all AI systems function the same way. One emerging concept is AI agents, which go beyond traditional AI models like ChatGPT.

What are AI Agents?How they differ from regular AI.ExampleApplicationsPython Implementation

An AI agent is a smart system that can understand its surroundings, make decisions, and take actions to reach a goal. It keeps learning, improving, and interacting with its environment based on set tasks.

Example:

A self-driving car is a great example of an AI agent

It understands its surroundings using cameras and sensors.It makes decisions like when to stop, turn, or speed up.It takes actions by steering, braking, or accelerating.It learns and adapts to new road conditions and traffic patterns over time.Self Driving Car Example

This shows how an AI agent works independently to achieve its goal — driving safely to a destination.

AI agents typically consist of the following components

Perception — Gathers data from sensors or digital inputs.Decision-making — Uses AI models, logic, or heuristics to determine actions.Action Execution — Performs tasks in response to inputs.Learning & Adaptation — Improves over… Read the full blog for free on Medium.

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Published via Towards AI