AI Series Ep. 7 🤖 | Types of Agents in Artificial Intelligence Explained Simply

In Episode 7 of our AI Series, we dive into one of the core concepts of Artificial Intelligence — Types of AI Agents — and explain them in a simple, structured way.

AI agents are systems that perceive their environment, make decisions, and act accordingly. In this episode, we cover five major types of agents, starting from the most basic to the most advanced.

🔍 Types of AI Agents Covered:

1️⃣ Simple Reflex Agent
– Acts purely based on current input
– Follows condition–action rules
– Best suited for fully observable environments

2️⃣ Model-Based Reflex Agent
– Maintains an internal model of the environment
– Can handle partially observable situations
– Makes smarter decisions than simple reflex agents

3️⃣ Goal-Based Agent
– Takes actions to achieve a specific goal
– Evaluates future states before acting
– Used in planning and problem-solving systems

4️⃣ Utility-Based Agent
– Chooses actions that maximize overall usefulness
– Balances multiple outcomes and preferences
– Widely used in real-world decision-making systems

5️⃣ Learning Agent
– Improves performance over time
– Learns from experience and feedback
– Forms the foundation of modern AI systems

📌 This episode is ideal for:
🎓 AI & Computer Science students
🤖 Beginners learning Artificial Intelligence
📚 Exam & interview preparation
💡 Anyone building a strong AI foundation

Watch till the end to clearly understand how AI agents work and why each type matters in real-world applications like robotics, automation, and intelligent systems.