Evidence Receipt. Related Resources.
Evidence Receipt. Related Resources.
Compared to this week’s papers
Verification pending
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Route this paper proof surface into REST, MCP, or developer workflows while preserving the same evidence receipt and related-resource context.
Page Freshness
Canonical route: /signal-canvas/shape-formation-for-the-cooperative-transportation-of-arbitrary-objects-using-multi-agent-reinforcement-learning
Page-specific freshness sourced from this paper's evidence receipt and score bundle.
Agent Handoff
Canonical ID shape-formation-for-the-cooperative-transportation-of-arbitrary-objects-using-multi-agent-reinforcement-learning | Route /signal-canvas/shape-formation-for-the-cooperative-transportation-of-arbitrary-objects-using-multi-agent-reinforcement-learning
REST example
curl https://sciencetostartup.com/api/v1/agent-handoff/signal-canvas/shape-formation-for-the-cooperative-transportation-of-arbitrary-objects-using-multi-agent-reinforcement-learningMCP example
{
"tool": "search_signal_canvas",
"arguments": {
"mode": "paper",
"paper_ref": "shape-formation-for-the-cooperative-transportation-of-arbitrary-objects-using-multi-agent-reinforcement-learning",
"query_text": "Summarize Shape Formation for the Cooperative Transportation of Arbitrary Objects Using Multi-Agent Reinforcement Learning"
}
}source_context
{
"surface": "signal_canvas",
"mode": "paper",
"query": "Shape Formation for the Cooperative Transportation of Arbitrary Objects Using Multi-Agent Reinforcement Learning",
"normalized_query": "2606.09610",
"route": "/signal-canvas/shape-formation-for-the-cooperative-transportation-of-arbitrary-objects-using-multi-agent-reinforcement-learning",
"paper_ref": "shape-formation-for-the-cooperative-transportation-of-arbitrary-objects-using-multi-agent-reinforcement-learning",
"topic_slug": null,
"benchmark_ref": null,
"dataset_ref": null
}Claims: 1
References: Pending verification
Proof: Verification pending
Freshness state: computing
Source paper: Shape Formation for the Cooperative Transportation of Arbitrary Objects Using Multi-Agent Reinforcement Learning
PDF: https://arxiv.org/pdf/2606.09610v1
Source count: 3
Coverage: 50%
Last proof check: 2026-06-09T03:24:27.438Z
Signal Canvas receipt window
/buildability/shape-formation-for-the-cooperative-transportation-of-arbitrary-objects-using-multi-agent-reinforcement-learning
Subject: Shape Formation for the Cooperative Transportation of Arbitrary Objects Using Multi-Agent Reinforcement Learning
Verdict
Ignore
Preparing verified analysis
Dimensions overall score 0.0
No public code linked for this paper yet.
{"file name": "input.pdf", "number of pages": 8, "author": "Mohamed Sayed; Wolfram Burgard; Tanja Katharina Kaiser"
Implication not extracted yet.
partial
Related resources will appear here when this paper maps cleanly to topic, benchmark, or dataset surfaces.
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Verdict is Ignore because current viability and proof state do not clear the buildability gate.
Time to first demo
Insufficient data
No first-demo timestamp, owner estimate, or elapsed demo receipt is attached to this surface.
Structured compute envelope
Insufficient data
No data, compute, hardware, memory, latency, dependency, or serving requirement receipt is attached.
Receipt path
/buildability/shape-formation-for-the-cooperative-transportation-of-arbitrary-objects-using-multi-agent-reinforcement-learning
Paper ref
shape-formation-for-the-cooperative-transportation-of-arbitrary-objects-using-multi-agent-reinforcement-learning
arXiv id
2606.09610
Generated at
2026-06-09T03:24:27.438Z
Evidence freshness
fresh
Last verification
2026-06-09T03:24:27.438Z
Sources
3
References
0
Coverage
50%
Lineage hash
f704300d9b889016a5020e54e54ce4b5cc5b91c3e1ebcdc9f27d0a84fd837222
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.
Pending verification refs / 3 sources / Verification pending
repo_url
references