Skip to content
Sagan

Paper

State Representation and Termination for Recursive Reasoning Systems

Unreadunread

AI summary

This paper tackles two design questions for recursive reasoning systems (systems that alternate between gathering evidence and refining understanding): how to represent the evolving state and when to stop iterating. The authors propose an epistemic state graph encoding claims, evidence, open questions, and confidence weights, and introduce the "order-gap"—the difference between expand-then-consolidate versus consolidate-then-expand. A small order-gap suggests the two orders agree and further iteration won't help. They provide a necessary and sufficient condition for the linearized order-gap to be informative (non-degenerate) near a fixed point, and sketch applications to agent loops, tree-of-thought, theorem proving, and continual learning.

Main takeaways:

  • Recursive reasoning systems need a state representation (epistemic state graph) and a stopping criterion (order-gap).
  • The order-gap measures whether expand-then-consolidate ≈ consolidate-then-expand; small gap means stop iterating.
  • A formal condition tells you when the order-gap is informative versus algebraically vacuous near the fixed point (local, not global).
  • Framework applies to agent loops, tree-of-thought reasoning, theorem proving, and continual learning.
  • Addresses the "when to stop" problem in iterative reasoning without relying on heuristics or fixed iteration counts.