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News/Beyond Scalar Rewards: Dense Feedback for LLM Policy Synthesis in Sequential Social Dilemmas
arxiv
PublishedJuly 1, 2026 at 4:00 AM
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Beyond Scalar Rewards: Dense Feedback for LLM Policy Synthesis in Sequential Social Dilemmas

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arxiv.orgfull article ↗
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Publisher summary· verbatim

arXiv:2603.19453v3 Announce Type: replace Abstract: We propose an LLM harness that generates code-based policy functions for multi-agent environments, evaluates them with self-play, and refines them using feedback from previous iterations. Following the recent line of work in feedback engineering (t

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Discussion
Mentioned models
02
  • 01
    Claude Sonnet 4.6
  • 02
    Gemini 3.1 Pro
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arxiv
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Tags
04
#multi-agent#feedback#game-theory#llm

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Mentioned models
02
  • 01
    Claude Sonnet 4.6
  • 02
    Gemini 3.1 Pro
Source
↗
arxiv
Read original ↗All from arxiv →
Tags
04
#multi-agent#feedback#game-theory#llm

Related coverage

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