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Evidence record 3504 · automatically gathered

Discovering Cooperative Pipelines: Autoresearch for Sequential Social Dilemmas

We study two-level autoresearch for cooperation: an outer-loop AI agent autonomously redesigns the inner-loop pipeline of an LLM policy-synthesis system for multi-agent Sequential Social Dilemmas (SSDs). A researcher agent $\mathcal{R}$ (run as a coding agent) reads the inner-loop source code, edits system prompts, feedback functions, helper libraries, and iteration logic, runs evaluations, and decides what to keep, following the autoresearch paradigm. Across two games (Cleanup and Gathering), t

Record details

Published: 28 May 2026
Source: arXiv
Category: Research
Topics: Regulation · Agents & autonomy
Retrieved: 14 July 2026

source-onlyevidence status

These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.

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How to cite this record

ethics.ai (28 May 2026), “Discovering Cooperative Pipelines: Autoresearch for Sequential Social Dilemmas,” evidence record 3504, https://ethics.ai/record/3504 (originally published by arXiv).

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