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pith:UOGG4A7B

pith:2026:UOGG4A7BLI5EOR2T7KKL4FOXTC
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Uncertainty-Aware Predictive Safety Filters for Probabilistic Neural Network Dynamics

Bernd Frauenknecht, Daniel Mayfrank, Henrik Hose, Lukas Kesper, Sebastian Trimpe

The Uncertainty-Aware Predictive Safety Filter uses reachable sets from probabilistic ensemble neural networks and an explicit certainty constraint to guarantee safety during model-based reinforcement learning exploration.

arxiv:2604.26836 v2 · 2026-04-29 · cs.LG · cs.SY · eess.SY

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Claims

C1strongest claim

We introduce the Uncertainty-Aware Predictive Safety Filter (UPSi), a PSF that provides rigorous safety predictions using PE dynamics models by formulating future outcomes as reachable sets. UPSi introduces an explicit certainty constraint that prevents model exploitation and integrates seamlessly into common MBRL frameworks.

C2weakest assumption

That reachable sets derived from probabilistic ensemble neural network predictions can be computed rigorously enough to guarantee constraint satisfaction, and that the certainty constraint sufficiently prevents exploitation of model uncertainty without overly restricting exploration.

C3one line summary

UPSi integrates probabilistic neural network dynamics into predictive safety filters via reachable sets and a certainty constraint, improving safety in model-based RL exploration while matching standard performance.

Receipt and verification
First computed 2026-05-22T02:04:41.422199Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

a38c6e03e15a3a474753fa94be15d798a506302743d3202bf64772510573b1b1

Aliases

arxiv: 2604.26836 · arxiv_version: 2604.26836v2 · doi: 10.48550/arxiv.2604.26836 · pith_short_12: UOGG4A7BLI5E · pith_short_16: UOGG4A7BLI5EOR2T · pith_short_8: UOGG4A7B
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Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/UOGG4A7BLI5EOR2T7KKL4FOXTC \
  | 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: a38c6e03e15a3a474753fa94be15d798a506302743d3202bf64772510573b1b1
Canonical record JSON
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    "abstract_canon_sha256": "20a65ff2808ec68cfdf146124da026fc790d885c7ad080d802ffb50160174bbe",
    "cross_cats_sorted": [
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    ],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "cs.LG",
    "submitted_at": "2026-04-29T16:01:59Z",
    "title_canon_sha256": "0ad2ee7877817b5067a1aa9cf10890d83ef3aa155eb6f0a1ae879792379e009f"
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