(Lec-59) Agents/Intelligent Agents | AI বাংলা টিউটোরিয়াল

Описание: What exactly is an Intelligent Agent in AI? In this video, we’ll introduce the concept of Agents and Intelligent Agents, the building blocks of modern Artificial Intelligence systems!

🧠 What you’ll learn:

What is an Agent in AI?

Key components: sensors, actuators, environment

What makes an agent intelligent?

Types of Intelligent Agents:
✔ Simple Reflex Agents
✔ Model-Based Reflex Agents
✔ Goal-Based Agents
✔ Utility-Based Agents
✔ Learning Agents

Real-world examples (AI in games, robots, virtual assistants, etc.)

🎯 Ideal for computer science students, AI enthusiasts, and beginners looking to build a strong foundation in Artificial Intelligence.

📌 Like, comment, and subscribe to Lecturelia for beginner-friendly AI and CS tutorials in Bangla and English.

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Agents in Artificial Intelligence
An AI system can be defined as the study of the rational agent and its environment. The agents sense the environment through sensors and act on their environment through actuators. An AI agent can have mental properties such as knowledge, belief, intention, etc.

What is an Agent?
An agent can be anything that perceiveits environment through sensors and act upon that environment through actuators. An Agent runs in the cycle of perceiving, thinking, and acting. An agent can be:

Human-Agent: A human agent has eyes, ears, and other organs which work for sensors and hand, legs, vocal tract work for actuators.
Robotic Agent: A robotic agent can have cameras, infrared range finder, NLP for sensors and various motors for actuators.
Software Agent: Software agent can have keystrokes, file contents as sensory input and act on those inputs and display output on the screen.
Hence the world around us is full of agents such as thermostat, cellphone, camera, and even we are also agents.

Before moving forward, we should first know about sensors, effectors, and actuators.

Sensor: Sensor is a device which detects the change in the environment and sends the information to other electronic devices. An agent observes its environment through sensors.

Actuators: Actuators are the component of machines that converts energy into motion. The actuators are only responsible for moving and controlling a system. An actuator can be an electric motor, gears, rails, etc.

Effectors: Effectors are the devices which affect the environment. Effectors can be legs, wheels, arms, fingers, wings, fins, and display screen.

Sensor: Sensor is a device which detects the change in the environment and sends the information to other electronic devices. An agent observes its environment through sensors.

Actuators: Actuators are the component of machines that converts energy into motion. The actuators are only responsible for moving and controlling a system. An actuator can be an electric motor, gears, rails, etc.

Effectors: Effectors are the devices which affect the environment. Effectors can be legs, wheels, arms, fingers, wings, fins, and display screen.

PEAS Representation
PEAS is a type of model on which an AI agent works upon. When we define an AI agent or rational agent, then we can group its properties under PEAS representation model. It is made up of four words:

P: Performance measure
E: Environment
A: Actuators
S: Sensors
Here performance measure is the objective for the success of an agent's behavior.

PEAS for self-driving cars:

Let's suppose a self-driving car then PEAS representation will be:

Performance: Safety, time, legal drive, comfort

Environment: Roads, other vehicles, road signs, pedestrian

Actuators: Steering, accelerator, brake, signal, horn

Sensors: Camera, GPS, speedometer, odometer, accelerometer, sonar.