In today's world, everything is running toward automation and Artificial Intelligence is one of the most important parts of it.
One of the most trending topics in this field is-
"Multi-Agent Systems"
Before directly jumping towards the Multi-Agent Systems, let me first introduce you to what an "Agent" is actually?
An agent can be any company, individual, or organization that can make independent decisions on its own by learning from the environment.
So what it means?
An easy explanation-
Let the agent is your pet dog.
The task is that you have thrown a stick in the garden and he has to pick it for you.
The environment is the garden in which you are playing with your dog.
So it will work like this, you throw a stick, the dog will run or not run towards the stick, and may or may not pick it up to you.
According to his action, you will reward the dog a treat or not.
So this is all about an agent in AI.
An agent will work in an environment toward a task and will learn through the rewards it gets whether it is a negative or a positive point.
Now come to MAS(Multi-Agent Systems).
As we talked about earlier, the agent works in an environment. But in the previous example, the environment contains only one agent, i.e, a dog.
Let us assume you are a pet lover and you may have 10s of dogs and you bring all 10 dogs into your garden so there are 10 agents in one single environment .i.e, a garden.
So the environment that contains more than one agent doing similar work with or without interacting with each other is known as Multi-Agent Systems.
What's the benefit of it?
Let us assume the dog your pet was lazy and he is bringing the stick back to you in hours and when 10 dogs came here others were fast as anything and bring it up to you in a second.
So the main benefit of a multi-agent system is the optimization and fast service.
It is better than a single optimization algorithm.
Real-world examples-
-> Service Robots
-> Transportation Systems
-> Rescue in Disaster Scenario
-> Exploration of hazardous environments
etc.