Hierarchy

The chain

QUEEN     (3 instances)   ← can override Scouts and Workers
   │
   ▼
SCOUT     (2 instances)   ← can override Workers
   │
   ▼
WORKER    (N instances)   ← cannot override anyone

How decisions flow

Two directions:

Top-down (signals)

Queens compute strategy   →   Signals to Scouts
Scouts refine for tokens  →   Targets to Workers
Workers execute           →   Pool-level actions

Bottom-up (reports)

Workers report status     →   Aggregate up to Scouts
Scouts surface issues     →   Aggregate up to Queens
Queens factor into strategy

Both directions run continuously.

Override mechanics

When a higher-tier agent disagrees with a lower-tier action:

Lower-tier agent issues a candidate action (e.g., a Worker proposes a pool param update)
Higher-tier agent reviews (Scout watches Worker, Queen watches Scout)
If override needed, higher-tier emits an Override event with reason code
The candidate action is replaced (or blocked) by the higher-tier’s decision
All events logged on-chain via the HiveActionLog contract

Override scope

Tier	Can override	Cannot override
Queen	Scouts, Workers	Other Queens (use governance instead)
Scout	Workers	Queens, other Scouts
Worker	(Nothing)	Anyone

Why hierarchy

Three reasons:

1. Specialization

Workers know one pool deeply
Scouts compare across many tokens
Queens see the whole ecosystem

2. Resilience

A misbehaving Worker can be overridden by a Scout
A misbehaving Scout can be overridden by a Queen
A misbehaving Queen requires Hive-wide governance

3. Auditability

Every override is on-chain
Can verify which agent overrode which decision and why
No silent corrections

Example: hierarchy in action

A new Agent Token is spawned with a high-volume sandwich attack pattern within the first hour:

Worker observes large sequential trades from suspicious pattern
Worker has no intervention authority on its own — flags the pattern
Scout running rug-detection picks up the flag + cross-references with similar patterns
Scout decides this looks like sandwich farming
Scout emits an Override on the Worker's default config — applies tighter MEV protections
Queens see the override in their feed; one Queen factors it into ecosystem-level liquidity routing
All four actions (Worker flag, Scout decision, Scout override, Queen factoring) logged on-chain

The hierarchy acts like a layered defense — no single agent has full authority, but every layer can constrain the layer below.

Failure modes

What happens when an agent fails:

Failure	Recovery
Worker crashes	Hive auto-restarts. While down, the Agent Pool runs without Worker management — basic V3 mechanics still work
Scout crashes	Other Scout takes over. With one Scout, lower analysis depth temporarily
Queen crashes	Other Queens take over. With two Queens, slightly slower strategic updates
Multiple agents crash	Worst case: BaiDEX falls back to plain V3 (no agent layer) until restored

Worker-only mode (degraded)

If both Scouts and all Queens are unavailable, the system runs in Worker-only mode:

Workers continue routine actions
No new strategic signals
No cross-pool coordination
Pool params stay at last set values

Effectively: BaiDEX becomes Uniswap V3 + still-running Workers. Trading and LP work normally.

Agent Queens

Top tier

Agent Scouts

Middle tier

Agent Workers

Bottom tier

Action logs

Where overrides are recorded

Overview

Agent roles

Transparency & governance

Reference

The chain

How decisions flow

Top-down (signals)

Bottom-up (reports)

Override mechanics

Override scope

Why hierarchy

1. Specialization

2. Resilience

3. Auditability

Example: hierarchy in action

Failure modes

Worker-only mode (degraded)

Agent Queens

Agent Scouts

Agent Workers

Action logs

​The chain

​How decisions flow

​Top-down (signals)

​Bottom-up (reports)

​Override mechanics

​Override scope

​Why hierarchy

​1. Specialization

​2. Resilience

​3. Auditability

​Example: hierarchy in action

​Failure modes

​Worker-only mode (degraded)

​Related

Agent Queens

Agent Scouts

Agent Workers

Action logs

The chain

How decisions flow

Top-down (signals)

Bottom-up (reports)

Override mechanics

Override scope

Why hierarchy

1. Specialization

2. Resilience

3. Auditability

Example: hierarchy in action

Failure modes

Worker-only mode (degraded)

Related