Proactive Service Agents: A Unified Decision Framework, Methods, and Evaluation

2026-09-03

AI Summary

论文提出了一种主动服务代理的决策框架，通过部分可观测的顺序决策过程解决环境和用户信号不完整时的服务机会推断问题。

Abstract

Large language model agents can plan, invoke tools, and modify external states, yet most systems still take an explicit user instruction as a fixed starting point. Proactive service moves the decision upstream: an agent must infer service opportunities from incomplete environmental and user signals, choose among remaining silent, asking, assisting, and acting, and account for interruption, misunderstanding, overreach, and privacy costs. This survey gives an operational definition centered on initiative and formulates the problem as a partially observable sequential decision process constrained by authorization and risk. The formulation represents timing, content, and delivery within one structured action, while making explicit the option value of waiting, the decision value of questions, and feedback-induced state changes. On this basis, we organize existing methods along one decision pipeline (state and need estimation, intervention gating, action construction, and feedback adaptation) and describe prescribed, predictive, model based, and return optimizing mechanisms as nonexclusive policy-construction components. We further normalize decision units and three-axis evidence descriptors across streaming dialogue, screen, video, software-engineering, and human-agent collaboration resources, and formalize metrics for triggering, timing, calibration, user burden, safety, and policy value. The synthesis shows why offline classification performance alone does not predict deployment benefit and why long-term memory is not a defining condition of proactivity. Reliable proactive service instead requires calibrated incremental intervention value, verifiable authorization, recoverable execution, and counterfactual evidence.

Problem

• Proactive Service
• Large Language Model Agents
• Decision Framework
• Service Opportunities
• User Signals

Innovation

• Proactive Service
• Partially Observable Sequential Decision Process
• Authorization and Risk Constraints
• Incremental Intervention Value
• Counterfactual Evidence