Category: agents
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Pi Agent：Containerization 与 Compaction
TLDR: Coding agents need sandboxed execution, context compaction, and continuation mechanics so long-running work can survive safely across many tool calls.
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MAS Conference Papers：近期多智能体系统论文阅读清单
TLDR: This page is a ranked reading shortlist for recent MAS papers, prioritizing collaboration structure, topology design, runtime efficiency, and verification.
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Beyond Individual Intelligence：LLM-based Multi-Agent Systems 的 LIFE 框架
TLDR: The LIFE survey reframes LLM multi-agent systems as a lifecycle: build individual capability, integrate collaboration, attribute failures, then evolve the system.
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Concordia：用 LLM Agent 搭建可干预的社会模拟
TLDR: Concordia treats LLM agents as situated social actors with memory, roles, and norms, making simulations easier to observe and intervene in than plain chat swarms.
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Autocurricula and Multi-Agent Innovation：社会互动如何生成新问题
TLDR: Multi-agent intelligence should study how cooperation, competition, specialization, and shared discoveries create abilities that isolated agents would miss.
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Social Dilemmas：三个经典社会困境
TLDR: Social dilemmas show why individually rational actions can damage group outcomes, and why cooperation depends on payoffs, repetition, reputation, and norms.
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A Social Path to Human-Like AI：社会互动如何生成新数据
TLDR: Human-like AI may require populations of agents learning through social interaction, where cooperation and competition generate skills beyond single-agent training.
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Building a C Compiler with Agent Teams
TLDR: A practical multi-agent software pipeline can stay simple: split compiler work across coding agents, isolate tasks, and judge progress with integration tests.