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State Representation and Termination for Recursive Reasoning Systems

Summary

This paper proposes representing the evolving reasoning state as an epistemic state graph and defines an 'order-gap' to decide when to stop iterating. A necessary and sufficient condition for the linearized order-gap to be non-degenerate near the fixed point is provided. Applications include agent loops, tree-of-thought reasoning, theorem proving, and continual learning.

SourcearXiv AIAuthor: Debashis Guha, Amritendu Mukherjee, Sanjay Kukreja, Tarun Kumar
State Representation and Termination for Recursive Reasoning Systems
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[2605.06690] State Representation and Termination for Recursive Reasoning Systems

[Submitted on 2 May 2026]

Title:State Representation and Termination for Recursive Reasoning Systems

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Abstract:Recursive reasoning systems alternate between acquiring new evidence and refining an accumulated understanding. Two design choices are typically left implicit: how to represent the evolving reasoning state, and when to stop iterating. This paper addresses both. We represent the reasoning state as an epistemic state graph encoding extracted claims, evidential relations, open questions, and confidence weights. We define the order-gap as the distance between the states reached by expand-then-consolidate versus consolidate-then-expand; a small order-gap suggests that the two orderings agree and further iteration is unlikely to help. Our main result gives a necessary and sufficient condition for the linearised order-gap to be non-degenerate near the fixed point, showing when the criterion is informative rather than algebraically vacuous. This is a local condition, not a global convergence guarantee. We apply the framework to recursive reasoning systems and sketch its application to agent loops, tree-of-thought reasoning, theorem proving, and continual learning.

Subjects:

Artificial Intelligence (cs.AI); Computation and Language (cs.CL); Machine Learning (cs.LG)

Cite as: arXiv:2605.06690 [cs.AI]

(or arXiv:2605.06690v1 [cs.AI] for this version)

https://doi.org/10.48550/arXiv.2605.06690

arXiv-issued DOI via DataCite

Submission history

From: Amritendu Mukherjee [view email] [v1] Sat, 2 May 2026 07:40:09 UTC (16 KB)

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Key points and analysis

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Key points

  • Reasoning state is represented as an epistemic state graph encoding claims, evidence, open questions, and confidence weights.
  • Order-gap measures disagreement between two expansion-consolidation orderings; a small gap suggests convergence.
  • Main result gives a local condition ensuring the gap is informative near the fixed point.
  • Framework applied to recursive reasoning systems with sketches for diverse AI domains.

Highlights and analysis are generated automatically and may contain errors. Check the original source.