AgentHive

Coordinate Thousands of Agents. Let Them Self-Organize.

Swarm intelligence + task allocation.

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What happens when you need to manage 50 agents?

Tasks get duplicated. Tasks get missed. Agents fight over resources. No clear hierarchy definition. Coordination cost grows exponentially with agent count.

The traditional approach is a centralized controller managing each agent.

But that doesn't scale.

Bees don't have a centralized coordinator. Bees have roles.

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Core Insight

AgentHive introduces Role-Based Agent Coordination:

• Each agent has a clearly defined role
• Role defines capabilities and responsibilities
• Agents self-organize based on role and task matching
• System emerges from individual behaviors

You don't need to control each agent. You just need to define roles.

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Three-Layer Architecture

┌─────────────────────────────────────────────────────────┐
│                      QUEEN                               │
│            High-level task allocation, role assignment,  │
│            monitoring                                    │
├─────────────────────────────────────────────────────────┤
│                     WORKERS                              │
│   [Analyst] [Builder] [Reviewer] [Executor] ...         │
│   Specialized roles, self-claiming from task pool        │
├─────────────────────────────────────────────────────────┤
│                      SCOUTS                              │
│   Discover new opportunities and threats, report to      │
│   Queen for role assignment                             │
└─────────────────────────────────────────────────────────┘

Queen Agent

• Receives high-level tasks
• Decomposes into role-based subtasks
• Assigns to suitable Workers
• Monitors progress and rebalances load

Worker Agent

• Has specialized capabilities
• Self-claims from task pool
• Reports completion to Queen
• Collaborates when tasks need multiple roles

Scout Agent

• Discovers new tasks and opportunities
• Monitors system health
• Reports anomalies to Queen

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Task Assignment Protocol

[Task Arrives] → [Queen Analyzes Requirements]
→ [Decompose into Subtasks] → [Match Worker Roles]
→ [Workers Self-Claim] → [Parallel Execution]
→ [Queen Aggregates Results] → [Deliver to User]

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Scaling to 100+ Agents

1. Role Pooling — Multiple agents per role, distribute tasks
2. Dynamic Rebalancing — Queen rebalances when Workers overload
3. Hierarchical Routing — Sub-Queens manage agent clusters
4. Self-Repair — Agent failure triggers automatic reassignment

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Quick Start

# Define roles
agenthive.create_role("analyst", capabilities=["data", "reasoning"])
agenthive.create_role("builder", capabilities=["code", "test"])
agenthive.create_role("reviewer", capabilities=["quality", "critique"])

# Queen receives task
task = "Analyze market and build prediction model"
queen.assign(task)

# Workers self-organize and execute
# Queen aggregates and delivers results

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The Philosophy

We believe:

• In swarm intelligence, roles are more important than rules
• Self-organization is better than centralized control
• Coordination should emerge from individual behavior, not be injected from the top

AgentHive is for:

• Teams needing to coordinate multiple specialized agents
• Tasks requiring dynamic allocation rather than static assignment
• Anyone wanting to scale from dozens to hundreds of agents

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The Spotlight

"While others struggle with 'how to coordinate 50 agents,' you only need to define 3 roles."

The key to swarm intelligence isn't controlling each individual — it's letting individuals find their roles.

That's the power of role-based coordination.

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Smarter group collaboration, not harder control.

AgentHive — Let agents find their roles.