Pith Number
pith:EORQBOGF
pith:2020:EORQBOGFECERJKKUF55NW6TDS4
not attested
not anchored
not stored
refs pending
Causality and Batch Reinforcement Learning: Complementary Approaches To Planning In Unknown Domains
arxiv:2006.02579 v1 · 2020-06-03 · cs.LG · cs.AI
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{EORQBOGFECERJKKUF55NW6TDS4}
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.
Cited by
Receipt and verification
| First computed | 2026-07-05T01:07:57.931744Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
23a300b8c5208914a9542f7adb7a63970ac20b150f5c93714cbdecd7f8f42bfa
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/EORQBOGFECERJKKUF55NW6TDS4 \
| 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: 23a300b8c5208914a9542f7adb7a63970ac20b150f5c93714cbdecd7f8f42bfa
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "b21197ee0add4e36ffe522ac54d9cb9d7b1284f5b1169e5053b7e0d206dd0e54",
"cross_cats_sorted": [
"cs.AI"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.LG",
"submitted_at": "2020-06-03T23:14:14Z",
"title_canon_sha256": "2868bee1c1be589ed604adedb88ffbf2650165690dc1ba0915be95db80f9d5c4"
},
"schema_version": "1.0",
"source": {
"id": "2006.02579",
"kind": "arxiv",
"version": 1
}
}