Incremental Residual Reinforcement Learning Toward Real-World Learning for Social Navigation

Incremental Residual Reinforcement Learning Toward Real-World Learning for Social Navigation | Signal Canvas | ScienceToStartup

Page Freshness

Signal Canvas proof surface

Canonical route: /signal-canvas/incremental-residual-reinforcement-learning-toward-real-world-learning-for-social-navigation

stale

Proof freshness: stale
Proof status: unverified
Display score: 7/10
Last proof check: 2026-04-10
Score updated: 2026-04-10
Score fresh until: 2026-05-10
References: 0
Source count: 3
Coverage: 50%

This page is showing the last landed evidence receipt and score bundle because the latest proof data is outside the freshness window.

Agent Handoff

Canonical ID incremental-residual-reinforcement-learning-toward-real-world-learning-for-social-navigation | Route /signal-canvas/incremental-residual-reinforcement-learning-toward-real-world-learning-for-social-navigation

REST example

curl https://sciencetostartup.com/api/v1/agent-handoff/signal-canvas/incremental-residual-reinforcement-learning-toward-real-world-learning-for-social-navigation

MCP example

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  }
}

source_context

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  "paper_ref": "incremental-residual-reinforcement-learning-toward-real-world-learning-for-social-navigation",
  "topic_slug": null,
  "benchmark_ref": null,
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Evidence Receipt

Route status: building

Claims: 0

References: Pending verification

Proof: Verification pending

Freshness state: computing

Source paper: Incremental Residual Reinforcement Learning Toward Real-World Learning for Social Navigation

PDF: https://arxiv.org/pdf/2604.07945v1

Source count: 3

Coverage: 50%

Last proof check: 2026-04-10T17:39:36.473Z

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Watch and verify: Incremental Residual Reinforcement Learning Toward Real-World Learning for Social Navigation

/buildability/incremental-residual-reinforcement-learning-toward-real-world-learning-for-social-navigation

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Subject: Incremental Residual Reinforcement Learning Toward Real-World Learning for Social Navigation

Verdict

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Verdict is Watch because viability or proof quality is intermediate and should be re-evaluated before execution.

Incremental Residual Reinforcement Learning Toward Real-World Learning for Social Navigation

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