In this article Learn the structure of agents in Artificial Intelligence, including key components such as sensors, actuators, percepts, agent function, agent program, and knowledge base. Understand how intelligent agents perceive, reason, and act through the perception–action cycle with real-world examples.
Structure of Agents in Artificial Intelligence
Introduction
An agent is an entity that perceives its environment and takes actions to achieve its goals.
The main function of an agent is to receive information through its sensors, process or interpret it, and then perform the appropriate action using its actuators.
Agent = Sensor + Actuator + Knowledge + Decision-Making Mechanism
General Structure of an Agent
The internal structure of an agent consists of the following main components:
1. Sensors
Sensors are devices that help the agent obtain information from its environment.
They can recognize elements of any physical or virtual world.
Examples:
- In a self-driving car: camera, radar, GPS
- In a vacuum cleaner robot: dust sensor
2. Actuators
Actuators are the components that enable an agent to act on the environment.
They convert the agent’s decisions into physical actions.
Examples:
- In a self-driving car: steering, brakes, accelerator
- In a robot: motors and wheels
3. Percept
A percept is the input received by a sensor from the environment.
It provides information about the current state.
Example:
If a vacuum cleaner’s sensor detects that the floor is dirty, that information is called a percept.
4. Percept Sequence
This is the sequence of all percepts received so far.
An agent makes decisions based on both its previous and current percepts.
Example:
Previous room cleaning status + current room status → decision on where to clean next.
5. Agent Function
An Agent Function is a mathematical mapping that defines the relationship between percepts and actions.
It determines which action should be performed in a given situation.
Example:
If the percept is “floor is dirty,” then the action = “cleaning.”
Agent Function:
f : Percept Sequence → Action
6. Agent Program
An Agent Program is the software implementation of the agent function.
It executes the decision-making process within a computer or machine.
Example:
A robot’s control software that takes sensor data and commands the motor to operate.
Internal Architecture of an Agent
Working of an Agent
An agent continuously follows a Perception–Action Cycle:
- Perceive: Receive input from the environment through sensors
- Think: Analyze the received information and make a decision
- Act: Perform an action in the environment through actuators
This continuous process is known as the Perception–Action Cycle.
Knowledge Base of an Agent
The Knowledge Base is a collection of all the information and rules available to the agent.
It stores:
- The current state of the environment
- Past experiences
- Possible actions
This knowledge enables the agent to make intelligent and rational decisions.
Examples of Agent Structure
Example 1: Self-Driving Car
| Component | Description |
| Sensors | Camera, GPS, Lidar |
| Actuators | Brakes, Steering, Accelerator |
| Percept | Road conditions, traffic signals |
| Knowledge Base | Road maps, traffic rules |
| Agent Program | Decision-making algorithm (AI software) |
Example 2: Intelligent Vacuum Cleaner
| Component | Description |
| Sensors | Dust sensor, collision sensor |
| Actuators | Motor, wheels |
| Percept | Floor dirty or clean |
| Agent Function | “Dirty” → “Clean” |
| Performance Measure | Room cleanliness |
Conclusion
The structure of an agent includes key components such as Sensors, Actuators, Percept, Agent Function, Agent Program, and Knowledge Base. Together, these components enable the agent to perceive, analyze, and act on its environment intelligently and effectively. This structured interaction between perception, reasoning, and action is what makes an agent truly intelligent.
POP- Introduction to Programming Using ‘C’
OOP – Object Oriented Programming
DBMS – Database Management System
RDBMS – Relational Database Management System
https://defineinfoloop.blogspot.com/?m=1