How Intelligent Agent work Inside?

An agent’s internal workings involve Agent program that run on computing device and process the data comes from the environment through its architecture. Let’s discuss how an agent works from the inside using program and architecture:

1. Agent architecture

1. Environment: Environment is the area around the agent that it interacts with. An environment can be anything like a physical space, a room or a virtual space like a game world or the internet.
2. Sensors: Sensors are tools that AI agent uses to perceive their environment. They can be any physical like cameras, microphones, temperature sensors or a software sensor that read data from files.
3. Actuators: Actuators are tools that AI agent uses to interact with their environment through some actions. They can be any physical actuators like wheels, motors, robotic hands, or computer screens or they can be software actuators that send messages.
4. Effectors: Effectors take instructions from decision making mechanism and translates them into actions and these actions are performed through actuators.

2. Program or Decision-making mechanism:

This is the brain of the AI agent, this mechanism processes the information that is received through sensors and makes decisions through that data using programs. Let’s understand how the agent’s program execute the operations.

• The decision-making mechanism, often referred to as the agent’s program, processes information from sensors and makes decisions based on that data.
• The program takes current percepts as input and generates actions for the actuators.
• It embodies the agent function, which maps percepts to actions based on the agent’s goals and objectives.
• Various types of agent programs exist, such as simple reflex agents, model-based reflex agents, goal-based agents, and utility-based agents.
• These programs differ in how they process percepts and generate actions, depending on the agent’s design and task requirements.

For example, a simple reflex agent may have a program that directly maps percept states to actions without considering past or future percepts for a two-state vacuum environment. This decision will be executed through effectors.

In the realm of AI, Intelligent Agents stand as pivotal entities, driving automation and decision-making with cognitive abilities. This article explores the concept, architecture, functionalities, and real-world applications of these agents, shaping the modern AI landscape.