ADR-CE-018: Pattern-to-Restriction Bridge

Status: Accepted Date: 2026-01-22 Parent: ADR-014 Coherence Engine Architecture

Context

RuvLLM's ReasoningBank stores successful patterns with verdicts. Prime-Radiant's restriction maps define constraints. These can reinforce each other:

Successful patterns → what "coherence" looks like
Failed patterns → what "incoherence" looks like

Decision

ReasoningBank patterns feed learned restriction map training.

Bridge process:

impl PatternToRestrictionBridge {
    fn learn_from_verdict(&mut self, pattern_id: PatternId, verdict: Verdict) {
        if verdict.success_score > 0.8 {
            // Success: train ρ to produce zero residual
            self.restriction_maps[pattern_id]
                .train(source, target, zero_residual);
        } else {
            // Failure: train ρ to produce high residual
            self.restriction_maps[pattern_id]
                .train(source, target, failure_residual);
        }
    }
}

Consequences

Benefits

Experience improves constraint accuracy
Successful patterns define "good" coherence
Failed patterns help detect future failures

Risks

Biased patterns lead to biased constraints
Need sufficient positive and negative examples

References

ADR-014: Coherence Engine Architecture, "RuvLLM Integration"
ruvllm/src/reasoning_bank/

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