Category: agents
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Concordia: LLM agents as social simulation actors
Concordia is useful because it treats LLM agents as situated social actors with memory, roles, norms, partial observations, and a world state mediated by a Game Master.
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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
The C compiler experiment worked because the project had the right substrate for agents: a modular architecture, objective tests, Git as shared memory, task locks, readable logs, and oracles that turned one giant goal into many local failures.
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Claude Code Auto Mode: permissions as runtime safety
Claude Code auto mode is not just fewer confirmation prompts. It is a runtime safety design that separates low-risk actions, intent-aware classification, prompt-injection defenses, and recovery after denial.