ANTMAN: Adaptive Need Tracking for Multi-Agent Navigation in Large Information Spaces
ANTMAN's Need Graph keeps multi-agent coordination nearly flat, rising 1.23x when searchable context grows 16x.
ANTMAN is an adaptive multi-agent framework that coordinates around unresolved information needs instead of static partitions of a large search space. A revisable Need Graph tracks requirements, accumulated evidence, prior attempts, and progress, then controls worker selection, routing, and task-local recovery. The policy is separated from substrate-specific search interfaces. Under a 16x increase in searchable context, active coordination rose only 1.23x versus more than 15x for partition-driven baselines, while answer quality stayed strong.
- Need Graph tracks unresolved requirements, evidence, attempts, and progress
- Same coordination policy works across different search interfaces
- 16x more context raised coordination only 1.23x versus over 15x
- Quality holds when substantially smaller worker models execute search
From the original article
1 min read at huggingface.co
Information-seeking agents increasingly operate over information spaces that are too large to process exhaustively. Yet many multi-agent systems organize computation around static partitions of the available space, causing coordination to grow with how information is segmented rather than with what the query still requires.
By Jerry Wang, Haibo Jin, Xiaopeng Yuan · huggingface.co
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