Simple reflex agents versus other types of AI agents

[Ehsanuls55]

AI agents are divided into many types and classes based on their capabilities, their mode of action (reactive or proactive), and their environment (static or dynamic).

The other three AI agents include:

Utility-based agents
Model-based reflex agents
Goal-based reflex agents
1. Model-based reflex agents
Model-based reflex agents can make decisions and take actions even if they do not have a complete view of what is happening around them.

Working mechanism:

These mid-level agents have a “mental map” (aka internal state) that is continually updated with hospital mailing email list new information from sensors. So even if they can only see part of what’s going on, or if the world changes without them knowing, they can keep track of things and make educated guesses about what might happen next.

**Unlike a simple reflex agent, which only reacts to what it sees at the moment, a model-based reflex agent thinks ahead and adapts its actions based on past experiences.

Example: Imagine a model-based agent in a maze game. It doesn't just blindly follow predefined navigation rules, but secretly consults the internal model to correlate the maze layout and the treasure location.

As the game progresses and new clues emerge, the agent updates his mental map, ready to avoid wrong turns and dead ends and claim the treasure.