Pith Number

pith:FNN4BC7A

pith:2026:FNN4BC7ATDAHTUA3IXS3MDSQ6S

not attested not anchored not stored refs pending

Reward Shaping and Action Masking for Compositional Tasks using Behavior Trees and LLMs

Ankita Samaddar, Nicholas Potteiger, Taylor T. Johnson, Xenofon Koutsoukos

MRBTs generated by LLMs and verified by SMT solvers deliver reactive reward shaping plus action masking for compositional RL tasks.

arxiv:2605.05795 v2 · 2026-05-07 · cs.LG

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\usepackage{pith}
\pithnumber{FNN4BC7ATDAHTUA3IXS3MDSQ6S}

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Record completeness

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2 Internet Archive

3 Author claim open · sign in to claim

4 Citations open

5 Replications open

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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.

Claims

C1strongest claim

Experiments demonstrate successful generation and refinement of five MRBTs, consistently improving training efficiency and task success rates over baselines and MRBTs without action masking.

C2weakest assumption

That LLMs can reliably produce MRBTs that remain correct and modular across varying task objects, and that the derived logical specifications fully capture reactivity to subtask failure without missing edge cases.

C3one line summary

MRBTs generated via LLMs and verified by SMT solvers deliver modular, reactive reward shaping and action masking that improves RL training efficiency and success rates on compositional tasks.

Receipt and verification

First computed	2026-05-26T01:03:32.532198Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

2b5bc08be098c079d01b45e5b60e50f49725043afd7d4e7a7ef6498b355b44de

Aliases

arxiv: 2605.05795 · arxiv_version: 2605.05795v2 · doi: 10.48550/arxiv.2605.05795 · pith_short_12: FNN4BC7ATDAH · pith_short_16: FNN4BC7ATDAHTUA3 · pith_short_8: FNN4BC7A

Agent API

Resolver JSON Graph JSON Events JSON Schema Signing key

Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/FNN4BC7ATDAHTUA3IXS3MDSQ6S \
  | 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: 2b5bc08be098c079d01b45e5b60e50f49725043afd7d4e7a7ef6498b355b44de

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "757bfb908689a4aa58296cbda02a83c2b77526b5cc9d41cb3c5c1f62f5f82434",
    "cross_cats_sorted": [],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.LG",
    "submitted_at": "2026-05-07T07:33:08Z",
    "title_canon_sha256": "d254cb3e2c0fd7e68a776032074eefcc034387dba24834339a2746dcf27f921c"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.05795",
    "kind": "arxiv",
    "version": 2
  }
}