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\begin{thebibliography}{99}
\small
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\bibitem{chern} M. Cherniavskii, D. Gribanov, D. Malyshev and P. M. Pardalos. \emph{Delta-modular ILP Problems of Bounded Codimension, Discrepancy, and Convolution}. arXiv:2405.17001v5, 2025. \url{https://arxiv.org/abs/2405.17001}.
\bibitem{master} J. Master. \emph{How to Compose Shortest Paths}. arXiv:2205.15306v2, 2022. \url{https://arxiv.org/abs/2205.15306}.
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\bibitem{niepert} M. Niepert. \emph{Markov Chains on Orbits of Permutation Groups}. UAI 2012; arXiv:1206.5396. \url{https://arxiv.org/abs/1206.5396}.
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\bibitem{gvozdanovic} I. Gvozdanović and S. Petrović. \emph{Learning to Sample Fibers for Goodness-of-Fit Testing}. Algebraic Statistics 17, 33--73, 2026; preprint first posted 2024. \url{https://arxiv.org/abs/2405.13950}.
\bibitem{diskin} Z. Diskin. \emph{General Supervised Learning as Change Propagation with Delta Lenses}. FoSSaCS 2020, LNCS 12077, 177--197; corrected extended version arXiv:1911.12904v4, 2021. \url{https://arxiv.org/abs/1911.12904}.
\bibitem{crainic} M. Crainic. \emph{On the Perturbation Lemma, and Deformations}. arXiv:math/0403266, 2004. \url{https://arxiv.org/abs/math/0403266}.
\bibitem{lafferriere} G. Lafferriere and H. Sussmann. \emph{Motion Planning for Controllable Systems Without Drift}. IEEE International Conference on Robotics and Automation 2, 1148--1153, 1991. \url{https://www.researchwithrutgers.org/en/publications/motion-planning-for-controllable-systems-without-drift/}.
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\bibitem{godel} J. Schmidhuber. \emph{Gödel Machines: Self-Referential Universal Problem Solvers Making Provably Optimal Self-Improvements}. arXiv:cs/0309048, revised 2006; related published versions 2005--2006. \url{https://arxiv.org/abs/cs/0309048}.
\bibitem{dreamcoder} K. Ellis et al. \emph{DreamCoder: Growing Generalizable, Interpretable Knowledge with Wake-Sleep Bayesian Program Learning}. arXiv:2006.08381, 2020. \url{https://arxiv.org/abs/2006.08381}.
\bibitem{metz} L. Metz, C. D. Freeman, N. Maheswaranathan and J. Sohl-Dickstein. \emph{Training Learned Optimizers with Randomly Initialized Learned Optimizers}. arXiv:2101.07367, 2021. \url{https://arxiv.org/abs/2101.07367}.
\bibitem{dgm} J. Zhang, S. Hu, C. Lu, R. Lange and J. Clune. \emph{Darwin Gödel Machine: Open-Ended Evolution of Self-Improving Agents}. arXiv:2505.22954v3, revised 12 March 2026. \url{https://arxiv.org/abs/2505.22954}.
\bibitem{aide} D. Srikanth, B. Zhao, D. Xu, Y. Wu and Z. Jiang. \emph{Recursive Self-Improvement of AI Research Agents}. arXiv:2609.26457, 22 September 2026. \url{https://arxiv.org/abs/2609.26457}.
\end{thebibliography}