diff --git a/docs/swarms/concept/swarm_architectures.md b/docs/swarms/concept/swarm_architectures.md index 174f95d6..293e58cb 100644 --- a/docs/swarms/concept/swarm_architectures.md +++ b/docs/swarms/concept/swarm_architectures.md @@ -6,10 +6,11 @@ A Hierarchical Swarm architecture organizes the agents in a tree-like structure. Higher-level agents delegate tasks to lower-level agents, which can further divide tasks among themselves. This structure allows for efficient task distribution and scalability. **Use-Cases:** + - Complex decision-making processes where tasks can be broken down into subtasks. + - Multi-stage workflows such as data processing pipelines or hierarchical reinforcement learning. -**Mermaid Graph:** ```mermaid graph TD A[Root Agent] --> B1[Sub-Agent 1] @@ -31,7 +32,6 @@ In a Parallel Swarm architecture, multiple agents operate independently and simu - Tasks that can be processed independently, such as parallel data analysis. - Large-scale simulations where multiple scenarios are run in parallel. -**Mermaid Graph:** ```mermaid graph LR A[Coordinator Agent] --> B1[Sub-Agent 1] @@ -49,9 +49,9 @@ A Sequential Swarm architecture processes tasks in a linear sequence. Each agent **Use-Cases:** - Workflows where each step depends on the previous one, such as assembly lines or sequential data processing. + - Scenarios requiring strict order of operations. -**Mermaid Graph:** ```mermaid graph TD A[First Agent] --> B[Second Agent] @@ -68,9 +68,9 @@ In a Round Robin Swarm architecture, tasks are distributed cyclically among a se **Use-Cases:** - Load balancing in distributed systems. + - Scenarios requiring fair distribution of tasks to avoid overloading any single agent. -**Mermaid Graph:** ```mermaid graph TD A[Coordinator Agent] --> B1[Sub-Agent 1] @@ -92,9 +92,9 @@ A Federated Swarm architecture involves multiple independent swarms collaboratin **Use-Cases:** - Distributed learning systems where data is processed across multiple nodes. + - Scenarios requiring collaboration between different teams or departments. -**Mermaid Graph:** ```mermaid graph TD A[Central Coordinator] @@ -124,9 +124,9 @@ A Star Swarm architecture features a central agent that coordinates the activiti **Use-Cases:** - Centralized decision-making processes. + - Scenarios requiring a central authority to coordinate multiple workers. -**Mermaid Graph:** ```mermaid graph TD A[Central Agent] --> B1[Peripheral Agent 1] @@ -144,9 +144,9 @@ A Mesh Swarm architecture allows for a fully connected network of agents where e **Use-Cases:** - Complex systems requiring high fault tolerance and redundancy. + - Scenarios involving dynamic and frequent communication between agents. -**Mermaid Graph:** ```mermaid graph TD A1[Agent 1] --> A2[Agent 2] @@ -166,9 +166,9 @@ A Cascade Swarm architecture involves a chain of agents where each agent trigger **Use-Cases:** - Multi-stage processing tasks such as data transformation pipelines. + - Event-driven architectures where one event triggers subsequent actions. -**Mermaid Graph:** ```mermaid graph TD A[Trigger Agent] --> B[Agent 1] @@ -186,9 +186,9 @@ A Hybrid Swarm architecture combines elements of various architectures to suit s **Use-Cases:** - Complex workflows requiring a mix of different processing strategies. + - Custom scenarios tailored to specific operational requirements. -**Mermaid Graph:** ```mermaid graph TD A[Root Agent] --> B1[Sub-Agent 1]