Requesting Expert Reasoning: Augmenting LLM Agents with Learned Collaborative Intervention

Researchers introduce AHCE (Active Human-Augmented Challenge Engagement), a framework that enables AI agents to collaborate with human experts more effectively through learned policies. The system achieved 32% improvement on normal difficulty tasks and 70% on difficult tasks in Minecraft experiments by treating humans as interactive reasoning tools rather than simple help sources.

• →LLM-based agents struggle in specialized domains due to missing long-tail knowledge from their training data.
• →The AHCE framework uses a Human Feedback Module with learned policies to optimize human-AI collaboration.
• →Testing in Minecraft showed 32% improvement on normal tasks and nearly 70% on highly difficult tasks.
• →The approach requires minimal human intervention while significantly boosting task success rates.
• →Success comes from learning how to request expert reasoning rather than just asking for help.