Pith Number
pith:MWJFM7C4
pith:2017:MWJFM7C4QTQDFWR3DXGZNXTU3H
not attested
not anchored
not stored
refs pending
A Comparison of Reinforcement Learning Techniques for Fuzzy Cloud Auto-Scaling
arxiv:1705.07114 v1 · 2017-05-19 · cs.DC · cs.AI
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{MWJFM7C4QTQDFWR3DXGZNXTU3H}
Prints a linked badge after your title and injects PDF metadata. Compiles on arXiv. Learn more · Embed verified badge
Record completeness
1
Bitcoin timestamp
2
Internet Archive
3
Author claim
· sign in to
claim
4
Citations
5
Replications
✓
Portable graph bundle live · download bundle · merged
state
The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same
current state with the deterministic merge algorithm.
Receipt and verification
| First computed | 2026-05-18T00:44:10.593213Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
6592567c5c84e032da3b1dcd96de74d9ddcbdafb4e1821f3305df41fa80d34a1
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/MWJFM7C4QTQDFWR3DXGZNXTU3H \
| 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())"
# expect: 6592567c5c84e032da3b1dcd96de74d9ddcbdafb4e1821f3305df41fa80d34a1
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "c33cb35e2c6dd26467f58110e668896f233a22e3310346ba5350d071dbaa8f74",
"cross_cats_sorted": [
"cs.AI"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.DC",
"submitted_at": "2017-05-19T17:56:42Z",
"title_canon_sha256": "dd60d4205088f5879d323710332a9021ca2bdbfdb185055ed76802dc1ca4651a"
},
"schema_version": "1.0",
"source": {
"id": "1705.07114",
"kind": "arxiv",
"version": 1
}
}