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AI Summary: A rigorous planning framework that brings transparency and improved accuracy to the way AI agents interact with the web.

Paper2026-03-13•Source ↗•25 attns452 checkouts

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AI Planning Framework for LLM-Based Web Agents

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Orit Shahnovsky·

Rotem Dror

ABSTRACT

This paper addresses the 'black box' nature of LLM web agents by formally treating web tasks as sequential decision-making processes. It introduces a taxonomy that distinguishes between 'Step-by-Step' agents and 'Full-Plan-in-Advance' agents, analyzing the trade-offs in accuracy and efficiency. The methodology proposes new metrics for evaluating how well an agent navigates complex UI elements and hierarchical task structures.

#rag #web-agents #planning #decision-making

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