pith:XGSIUPSI
Distributional Learning of Graph Languages Generated by Fixed-Interface Clause Systems
Fixed-parameter graph languages generated by clause systems are learnable in the limit from positive data and membership queries.
arxiv:2604.26333 v2 · 2026-04-29 · cs.FL
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Record completeness
Claims
Hence, for every fixed parameter tuple (Δ,m,s,t,w,d), the target language is identifiable in the limit from positive data and membership queries. We also prove that the learner has polynomial-time update on FICSL^FCP_Δ(m,s,t,w,d).
The target language belongs to the bounded class FICSL^FCP_Δ(m,s,t,w,d) that satisfies the finite context property under the bounded-degree assumption.
Graph languages from fixed-interface clause systems with the finite context property are identifiable in the limit from positive data and membership queries by a polynomial-time learner for any fixed bound tuple (Δ,m,s,t,w,d).
Receipt and verification
| First computed | 2026-06-09T01:05:18.294448Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
b9a48a3e487a921d4bf0ddcb83b09660afef2c430ec75aabd63744b413aa8f27
Aliases
· · · · ·Agent API
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curl -sH 'Accept: application/ld+json' https://pith.science/pith/XGSIUPSIPKJB2S7Q3XFYHMEWMC \
| jq -c '.canonical_record' \
| python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
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Canonical record JSON
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