Applications Of Multi Agent Systems, Benefits & Challenges
Multiple artificial intelligence (AI) agents cooperating to carry out activities on behalf of a user or another system make up a multiagent system (MAS)
An agent may have access to web searches, application programming interfaces (APIs), and external datasets
Different architectures can run multiagent systems. In centralised networks, a central unit links agents, controls data, and stores global knowledge
Instead of exchanging information with a global knowledge base, agents in decentralized networks exchange information with their neighbors
Agents in a hierarchical framework have different degrees of autonomy and resemble trees. One agent can make all of the decisions in a basic hierarchical system
Multiagent systems coordinate complex transportation networks through communication, cooperation, planning, and real-time information access
Multiagent systems can link the elements of supply chain management by utilising their extensive data resources, adaptability, and scalability
Multiagent systems can mimic possible threats by using their tools. Simulations of maritime attacks are one example