推荐系统正从服务人类转向服务人与代理的混合环境。
A Position Paper on Recommender Systems in the Era of Autonomous Agents
- 将智能代理视为独立的用户助手，而非平台组件
- 提出人、代理与平台间的三元交互关系模型
- 适合关注未来推荐系统架构的研究者
几十年来，推荐系统一直以服务人类用户为目标。然而，自主代理的快速部署带来了范式转变：推荐系统的消费者预计将越来越多地由人类和受授权代理共同构成。本文回顾了以往以人为中心的推荐系统研究，并阐述向这一混合环境过渡的趋势。我们把代理视为与用户对齐的独立助手，作为推荐系统的终端使用者，而非平台构建的组件。本文刻画了人类、代理与平台之间形成的三重互动关系，强调了这些关系间可能产生的动态变化。这一转变为推荐系统研究带来新机遇，同时也对评估、对齐与系统设计提出了独特挑战。
原文摘要 · Abstract (English)
For decades, recommender systems have been optimized to serve human users. However, the rapid deployment of autonomous agents introduces a paradigm shift: recommendation consumers are predicted to be increasingly a mixture of humans and authorized agents acting on their behalf. This position paper reviews insights from prior human-centric RecSys research and outlines the transition to this hybrid environment. In our discussion, we treat agents as independent, user-aligned assistants that act as end-users of recommender systems, rather than platform-built components. We characterize the resulting tripartite interactions among humans, agents, and platforms, highlighting the dynamics that can arise across these relationships. This shift presents new opportunities for RecSys research, while introducing unique challenges for evaluation, alignment, and system design.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。