RuleForge AI — Self-Evolving Internet-Learning Symbolic Engine
Assign a learning task, observe trusted sources, extract structured claims, generate symbolic rules, sandbox-test them, and let MetaObserver recommend the safest next direction.
Self-Evolving Internet-Learning Symbolic AI Engine
Internet gives experience. Symbolic rewriting creates structure. Testing creates truth. Memory creates growth. Meta-rules create intelligence.
RuleForge reads only approved sources, treats observations as evidence rather than truth, extracts structured claims, converts them into binary symbolic graphs, creates candidate rules, sandbox-tests them, and stores only decisions with an audit trail.
Internet Input Stream
Run a RuleForge cycle to read an approved source.
Core Loop
Extracted Knowledge
No claims extracted yet.
Symbolic Binary Graph
The 0/1 atom graph appears after extraction.
Generated Rules
No rules in this panel yet.
Sandbox Test Results
Sandbox results appear after rules are generated.
Rejected / Review Queue
No rules in this panel yet.
Active Laws
No rules in this panel yet.
Meta-Learning Layer
Meta-rules appear after sandbox decisions.
Memory + Audit
Memory fills after the first cycle.
Third-Person Strategist Watching RuleForge
MetaObserver does not create rules directly. It diagnoses RuleForge from above and recommends learning direction, experiments, mutations, retirements, and safety posture. Human approval is required before changing RuleForge behavior.
System Diagnosis
Waiting for RuleForge activity.
Next Recommended Path
Waiting for RuleForge activity.
Danger Warnings
No danger scan yet.
Breakthrough Signals
No breakthrough scan yet.
Strategy Q&A
Waiting for RuleForge activity.
Strategic Score Vector
Waiting for RuleForge activity.
Timeline of Strategic Decisions
Waiting for RuleForge activity.