Category: agents
-
Dynamic Workflows: from prompt to runtime
Dynamic Workflows reframes long-horizon agent work as runtime synthesis: split context, externalize state, verify intermediate outputs, and let the harness carry the parts a single prompt cannot reliably hold.
-
Pi Agent: containerization and compaction
Coding agents need two boundaries at the same time: an execution boundary that controls what they can do, and a context boundary that controls what they can remember across long work.
-
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.
-
Beyond Individual Intelligence: the LIFE frame for multi-agent systems
The LIFE survey is useful because it reframes LLM multi-agent systems as a lifecycle: build individual capability, integrate collaboration, attribute failures, and evolve the system.
-
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.
-
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.
-
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.
-
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.