会议信息

DAI 2026: International Conference on Distributed Artificial Intelligence

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截稿日期:
2026-07-27 已截稿
通知日期:
2026-09-16
会议日期:
2026-11-29
会议地点:
Hong Kong, China
届数:
CCF: C   浏览: 14136   关注: 3   参加: 0
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会伴指数 (CP-I)

57.6 / 100
全站第 708 名 / 共 5,759 个会议 · 前 13%

人工智能与机器学习 第 63 / 751

学术认可 (35%)
66
投稿选择性 (20%) 无数据 —— 按中性基准 50 分计入 —
会议传承 (20%)
59
社区关注 (10%)
44
资料公开度 (15%)
55

用到的输入: 收录等级：CCF C · 有据可查的届次：8 · 在会伴关注它的研究者：3 人 · 过去 24 个月打开过本页的研究者：56 人

公开资料里还缺: 历年录用率 (+4.5) · 最佳论文记录 (+2.3)
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置信度 80% —— 分数中有多大比例来自实际观测到的数据，而不是中性基准。 这个分数是怎么算出来的 · 查看完整榜单 · 算法版本 1.2 · 算于 2026-10-26

征稿

DAI 2026 (International Conference on Distributed Artificial Intelligence) is a CCF C conference held in Hong Kong, China on 2026-11-29. The paper submission deadline is 2026-07-27. Acceptance notifications are sent on 2026-09-16.

Scope and Topics of Interest Topics of interest include, but are not limited to, the following areas. Authors will be asked to select one or more relevant areas during submission. Agent Engineering & Infrastructure Agent frameworks, harnesses, and operating systems: LangGraph, AutoGen, CrewAI, Smolagents, OpenAI Agents SDK Memory architectures: long-term, short-term, episodic, factual, and experiential memory Skill acquisition and atomic skills Tool use: tool selection, grounding, and reliability Context engineering: context windows, compression, and selective retrieval Agent protocols: MCP, A2A, and interoperability standards AgentOps: observability, debugging, evaluation, and failure recovery Agent identity, reputation, and provenance Foundations of Agent Learning Reinforcement learning, multi-agent reinforcement learning, and cooperative or competitive learning Post-training for agents Self-play, curriculum, and open-ended learning Continual learning, meta-learning, and transfer Reward design and credit assignment Distributed, privacy-preserving, and collaborative learning Scaling laws and empirical theory of agent learning Self-Evolving & Self-Improving Agents Self-improvement and recursive self-modification Meta-reasoning and self-reflection Experience distillation: from trajectories to transferable knowledge Co-evolution of policies and critics Multi-agent evolutionary systems Gödel-style self-rewriting agents Benchmarks and evaluation for self-evolving systems Multi-Agent Cooperation & Human-Agent Interaction Cooperative multi-agent reinforcement learning, credit assignment, and teamwork Communication, language emergence, and negotiation LLM-based multi-agent orchestration Ad-hoc teamwork and zero-shot coordination Coalition formation and distributed problem solving Collective intelligence and swarm behavior Trust, explainability, and accountability AI agents as digital employees, collaborators, and competitors Human-agent and human-robot interaction Agent-based human interaction analysis Agents for enhancing human cooperation Game Theory, Economics & Agent Markets Algorithmic game theory and equilibrium computation Mechanism and market design, auctions, and social choice Strategic behavior of LLM agents and algorithmic collusion Machine-payable APIs and agent-to-agent transactions Contract theory and principal-agent models for AI Blockchain economics and decentralized systems Behavioral game models and bounded rationality Security games Embodied Multi-Agent Systems Multi-robot learning, coordination, and swarms Vision-Language-Action models for agent teams World models for multi-agent planning Sim-to-real transfer in multi-agent settings Heterogeneous embodied teams Safety layers and hardware-software co-design for physical agents Science of AI & AI for Science Science of AI Evaluation, benchmarking, and reproducibility of agent systems Interpretability of multi-agent LLM systems Emergent behavior, scaling laws, and phase transitions Failure modes, red-teaming, and safety evaluation Theoretical foundations of agentic AI AI for Science AI agents for scientific discovery AI agents in mathematics, physics, chemistry, biology, and materials Automated experiment design and execution Scientific literature understanding and hypothesis generation Human-agent collaborative research Agent-based simulation of societies Policy, governance, and alignment of agent collectives
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