A Relative-Computability Theory of Self-Improving Agents
Quick summary
arXiv:2605.27381v3 Announce Type: replace-cross Abstract: Agents increasingly modify the procedures by which they solve tasks and improve themselves. Autonomy over improvement, gains in practical capability, and enlargement of computational reach are distinct properties. We develop an oracle-relative model with mutable solvers, evaluators, and improvers. Uniform simulation keeps every total decision procedure produced by effective self-revision over $A$ within $\mathcal{C}(A)=\{D:D\leq_T A\}$; oracle joins account for additional access, while the relativized limit lemma separates limiting answ
Key takeaways
- arXiv:2605.27381v3 Announce Type: replace-cross Abstract: Agents increasingly modify the procedures by which they solve tasks and improve themselves.
- Autonomy over improvement, gains in practical capability, and enlargement of computational reach are distinct properties.
- We develop an oracle-relative model with mutable solvers, evaluators, and improvers.
Why it matters
“A Relative-Computability Theory of Self-Improving Agents” should be evaluated beyond branding and benchmark scores. Its practical importance will emerge in task accuracy, latency, unit cost, safety and integration with real workflows.
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