Pith Number
pith:5MJQHNNN
pith:2019:5MJQHNNN47GAZO6SYFGQNETJSD
not attested
not anchored
not stored
refs pending
Harnessing Reinforcement Learning for Neural Motion Planning
arxiv:1906.00214 v1 · 2019-06-01 · cs.RO · cs.LG · stat.ML
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{5MJQHNNN47GAZO6SYFGQNETJSD}
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
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claim
4
Citations
5
Replications
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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 | 2026-05-17T23:44:27.818911Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
eb1303b5ade7cc0cbbd2c14d06926990f4d55266a165a64ca6e7c8f76dc88b3d
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/5MJQHNNN47GAZO6SYFGQNETJSD \
| 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: eb1303b5ade7cc0cbbd2c14d06926990f4d55266a165a64ca6e7c8f76dc88b3d
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "0e919b15463f7bd65f36ab8f924b48460480ad5be7db28e14958e323c176f9b5",
"cross_cats_sorted": [
"cs.LG",
"stat.ML"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.RO",
"submitted_at": "2019-06-01T12:19:37Z",
"title_canon_sha256": "a11e7beffe022dade25bb4709087f5f8c1a358bcbd43b6de7210327fcc07fc42"
},
"schema_version": "1.0",
"source": {
"id": "1906.00214",
"kind": "arxiv",
"version": 1
}
}