A multi-agent system (MAS) is a group of intelligent agents that interact and work together towards achieving common goals. Agents in a MAS combine their individual capabilities and knowledge to collaborate on solving problems that are beyond the scope of any individual agent.
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Some key characteristics of a multi-agent system are:
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• Composed of multiple autonomous agents
• Agents have particular capabilities and expertise
• Agents communicate and coordinate with other agents
• Decentralized control and decentralized data
• Emergent global behavior from local agent interactions

Some of the key benefits of developing a multi-agent system are:

• Modularity - Agents can be added or removed as needed
• Robustness - System continues operation if some agents fail
• Scalability - Easy to expand system by adding agents
• Flexibility - Agents can be customized for different roles
• Faster problem solving - Parallelization of work across agents
• Broader intelligence - Combination of multiple skill sets

Relevance AI provides a no-code platform for easily building intelligent multi-agent systems. Here are the key steps:

• Identify the Goals and Scope - Define the objectives and outcomes you want to achieve an map out different tasks and workflows required.
• Create and Train Agents - Use pre-built agents or create custom agents. Train agents on specific domains and give them specialized skills
• Define Agent Interactions  - Model how agents will communicate and work together
• Deploy and Iterate - Deploy your multi-agent system. Monitor performance and add/adjust agents as needed