Verified earnings
$0.00
Potential queue
$0.00
Active work
0
Auto-ready
0
Brain cycles
0
Learned P(paid)
0.0%
Money brain
Bayesian outcome learning plus a bounded self-remodeling policy layer.
Next action
WAIT
Selection mode
—
Target
No safe target
Expected paid value
$0.00 · $0.00/h
Predicted P(paid)
0.0%
Payout route
VENUE MANAGED
Receiver
not configured
Learning rule
Waiting for first learning cycle
Last new outcomes learned
0
Execution result
waiting · no action
Self-remodeling architecture
The engine changes strategy and resource allocation from verified outcomes while hard safety gates stay fixed.
Earning phase
first payout
Champion policy
fast cash
Architecture cycles
0
Remodel events
0
Max solver hours
—
Competition tolerance
—
Exploration rate
0.0%
Goal weights
Preferred sources
learning
Quarantined sources
none
Preferred task classes
learning
Quarantined task classes
none
Learned target ranking
Ranked by the current champion policy, expected paid value/time, source reliability, competition, friction and payout route.
| Rank | Reward | P(paid) | Expected | $/hour | Target | Route |
|---|---|---|---|---|---|---|
| Waiting for the first adaptive ranking cycle. | ||||||
Cloud runner
GitHub Actions scans every 15 minutes; the solver performs deeper work on its own cycle.
Runner state
waiting
Workflow
axiom-bounty-control.yml
Last execution
No run yet
Execution policy
Hard gates before any automatic action.
direct payout preferredstrategy state may remodelexecutable self-rewrite disabled
Active process
Authoritative Frantic work and payout stage.
| Bounty | Status | Stage | Payout | Receipt |
|---|---|---|---|---|
| No authoritative work item in the latest snapshot. | ||||
Latest automatic actions
Claim/delivery events from the hunter.
No automatic action required in the latest cycle.
Live hunt queue
Potential value is never counted as earnings.
| Score | Reward | Mode | Candidate | Competition | Decision |
|---|---|---|---|---|---|
| No current candidates. | |||||