arXiv (All)
open access
Proactive Service Agents: A Unified Decision Framework, Methods, and Evaluation
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,
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Proteus: A Self-Evolving Red Team for Agent Skill Ecosystems#1116279
- Robots That Take Initiative: A Framework for Building and Evaluating Proactive Robots#1076566
- Foundations of Proactive Agents: Principles, Technical Layers, and Proactivity-Gym#1141311
- SAGE: A Statistical Acceptance Gate for Self-Evolving Agents#1130885
- DASH-OPD: Discrepancy-Aware Switching with Hysteresis for On-Policy Distillation#1070478
Record · ID 926618
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive