Buildability / Receipt
This public receipt window renders only fields present in the canonical receipt object, deterministic fixture receipt, or canonical evidence receipt. Missing compute, demo, hash, signature, approval, telemetry, and adoption fields stay explicit.
Public buildability page receipt window
/buildability/scalable-constrained-multi-agent-reinforcement-learning-via-state-augmentation-and-consensus-for-separable-dynamics
Subject: Scalable Constrained Multi-Agent Reinforcement Learning via State Augmentation and Consensus for Separable Dynamics
Verdict
Watch
Verdict is Watch because viability or proof quality is intermediate and should be re-evaluated before execution.
Time to first demo
Insufficient data
No first-demo timestamp, owner estimate, or elapsed demo receipt is attached to this surface.
Data
{"file name": "input.pdf", "number of pages": 30, "author": "Santiago Amaya-Corredor; Miguel Calvo-Fullana; Anders Jonsson"
Truth Boundary
Buildability surfaces only report computed viability and proof receipts. They do not claim live production usage, pilot outcomes, founder sign-off, public Brier calibration, judge divergence, or external adoption unless explicitly sourced.
Compute
{"file name": "input.pdf", "number of pages": 30, "author": "Santiago Amaya-Corredor; Miguel Calvo-Fullana; Anders Jonsson", "title": "Scalable Constrained Multi-Agent Reinforcement Learning via State Augmentation and Consensus for Separable Dynamics", "creation date": null, "modification date": null, "kids": []}
Inference
{"file name": "input.pdf", "number of pages": 30, "author": "Santiago Amaya-Corredor; Miguel Calvo-Fullana; Anders Jonsson", "title": "Scalable Constrained Multi-Agent Reinforcement Learning via State Augmentation and Consensus for Separable Dynamics", "creation date": null, "modification date": null, "kids": []}
Hardware
{"file name": "input.pdf", "number of pages": 30, "author": "Santiago Amaya-Corredor; Miguel Calvo-Fullana; Anders Jonsson", "title": "Scalable Constrained Multi-Agent Reinforcement Learning via State Augmentation and Consensus for Separable Dynamics", "creation date": null, "modification date": null, "kids": []}
Receipt path
/buildability/scalable-constrained-multi-agent-reinforcement-learning-via-state-augmentation-and-consensus-for-separable-dynamics
Paper ref
scalable-constrained-multi-agent-reinforcement-learning-via-state-augmentation-and-consensus-for-separable-dynamics
arXiv id
2605.30461
Generated at
2026-06-01T20:25:41.186Z
Evidence freshness
stale
Last verification
2026-06-01T20:25:41.186Z
Sources
4
References
0
Coverage
50%
Lineage hash
90eb006572f9de92dac817f5eeb6fa3bf1a82b5ab5057eb0e944f887b042fc9a
Canonical opportunity-kernel lineage hash.
External signature
unsigned_external
No founder, registry, pilot, or production-adoption signature is attached to this receipt.
Verification
not_verified
Verification is blocked until an external signature is provided.
Some score or evidence fields are outside the preferred freshness window.
references
proof_status