Swarms / docs /swarms /structs /multi_agent_orchestration.md
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Multi-Agent Orchestration:

Swarms was designed to faciliate the communication between many different and specialized agents from a vast array of other frameworks such as langchain, autogen, crew, and more.

In traditional swarm theory, there are many types of swarms usually for very specialized use-cases and problem sets. Such as Hiearchical and sequential are great for accounting and sales, because there is usually a boss coordinator agent that distributes a workload to other specialized agents.

Name Description Code Link Use Cases
Hierarchical Swarms A system where agents are organized in a hierarchy, with higher-level agents coordinating lower-level agents to achieve complex tasks. Code Link Manufacturing process optimization, multi-level sales management, healthcare resource coordination
Agent Rearrange A setup where agents rearrange themselves dynamically based on the task requirements and environmental conditions. Code Link Adaptive manufacturing lines, dynamic sales territory realignment, flexible healthcare staffing
Concurrent Workflows Agents perform different tasks simultaneously, coordinating to complete a larger goal. Code Link Concurrent production lines, parallel sales operations, simultaneous patient care processes
Sequential Coordination Agents perform tasks in a specific sequence, where the completion of one task triggers the start of the next. Code Link Step-by-step assembly lines, sequential sales processes, stepwise patient treatment workflows
Parallel Processing Agents work on different parts of a task simultaneously to speed up the overall process. Code Link Parallel data processing in manufacturing, simultaneous sales analytics, concurrent medical tests