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Chapter 2 · 2023

LLM-State: Open World State Representation for Long-horizon Task Planning with Large Language Model

Siwei Chen, Anxing Xiao, David Hsu

Abstract

This work addresses long-horizon task planning with LLMs in open-world household environments, where existing methods fail to explicitly track key objects and attributes. The paper proposes an open state representation that continuously expands and updates object attributes using the LLM's inherent capabilities for context understanding and historical action reasoning. This representation maintains a comprehensive record of object attributes and changes, enabling robust retrospective summaries and enhancing decision-making in task planning.

Eigenvector Insight — Zone III / PASF-PADE AnalysisNot part of the original paper
Eigenvector Research — Marco van Hurne
How this paper contributes to solving the Zone III problem (PASF-PADE)

This paper directly addresses one of the core structural challenges in Zone III deployments. The research on LLM, long-horizon task planning, state representation provides evidence-based foundations that enterprise architects cannot ignore when designing long-horizon autonomous workflows. The findings challenge the assumption that a base language model — however capable — can handle the complexity of durable, governed, multi-step execution without explicit architectural intervention. For Zone III practitioners, this paper belongs in the required reading list.

Why AI is not sufficient for Zone III without this

Zone III refers to high-complexity, high-risk, long-running agentic workflows — the class of enterprise AI deployments where a single failure can cascade across hundreds of steps. Standard AI models, trained to predict the next token, are not inherently designed for durable, governed, multi-step execution. This paper addresses one or more of the structural gaps that make Zone III deployments unsafe without explicit architectural intervention.

Topics

LLMlong-horizon task planningstate representationopen-world environmentsrobotics