Intelligent Multi Agent System Projects

Intelligent Multi Agent System Projects are the software or hardware agents that operate as better. At first, the Multi-Agent System is MAS that is interface with intelligent agents’ ability, and hence it is intelligent MAS. To be sure, the idea of intelligence into the MAS gives aid to work with mathematical methods, reinforcement learning, and many more. 

On the positive side, that is important to realize in intelligent MAS is that ‘it has a solution for all hard problems.’ The problem is like that; when a new report receives, it cannot make a decision without intelligence. 

In general, the agents can operate on three main environs, such as 1. Virtual, 2.Discrete, and 3. Continuous. Further, the three agent types are active, passive, and cognitive in Intelligent Multi-Agent System Projects. By now, we list the areas that each type of agent participates in a system as below.  

High Impact areas for Intelligent Multi-Agent System Projects

• Autonomous Microgrid
• The human with Robot and Agent communication 
• Smart grid for Energy Management 
• Wireless Sensor Networks
• Smart city 
• Internet of things 
• Smart agriculture  

   Earlier, the agents are potent to gather data from the environment, then analyze it and, at last, make a choice in it. In effect, the decision hangs on the artificial intelligence algorithm in-built in it. On the other hand, it is able to give the apt output for the system. 

Why use Artificial intelligence in MAS?

   In fact, the process of data analysis on any system will be only after the data collection. It seems to be in the past using which a choice will be. In order to needle out autonomous decision, the intelligence launches into MAS. And of course, it adapts many types of systems. 

Positiveness Achieved by Intelligent MAS

• Scalable at large scale systems
• Reliable decision making 
• Strong from any type of fault
• Suitable for a decentralized system 
• High efficiency in computation 

Know more about the Working of Intelligent MAS

   For instance, let the intelligent MAS be deployed in a grid, then the agents register first. Here in the case of a home system, it creates a number of agents as per the number of appliances. Thus it can be of agents for the fridge, rice cooker, AC, and so on. To be sure, the sensors on home appliances will sense and give the data to the agents. So then, the agent makes a decision either to turn ON or turn OFF or others.   

   Thus the agent will get the data, and then it gives a result whether the home appliance may go up the limit, faults, and many more so that the agents spread all over the machines in the system. Hence the decision is automatic using methods down. 

Know Main AI in Intelligent MAS 

• Artificial neural networks
  • Radial basis network
  • Multi-layer perceptron 
• Statistical learning methods
  • Decision tree
  • k-nearest neighbor 
• Probabilistic methods 
  • Kalman filter
  • Utility and also decision theory 

   As well it also aids with trust framework, anomaly detection, and others. Until now, the MAS is a response system that gives way out to every process. At this point, security is main since it is not only on a small scale. Still, it is wide, so this issue is significant.

Common Security threats in intelligent MAS

• Injection of fake task 
• Corrupted name of the agent 
• Unauthorized agent 
• Unauthorized host or the device in the system
• The compound attack, DoS attack, and so on

   So far, the need for security solves by safe communication, validating agents, and many more with communication projects in ns2. Now, as per the worth of data, it is mandated. Hence the MAS gives the best solution since it is efficient in data collection, fast, and so on.

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