# References and publication record

The numbered references below preserve the bibliography of **Bounded Agency and Reflective Freedom: Evaluative Revision, Information Limits, and Faithful Realization**. Citation numbers in its web chapters link here. Supplementary essays identify their own dependencies and do not assign the published paper credit for additional unpublished results.

The author-supplied publication is Jeremy Rodgers, Independent Researcher, 6 October 2026, Version 2.0. [DOI: 10.5281/zenodo.23202999](https://doi.org/10.5281/zenodo.23202999). [Read the supplied PDF](/publications/consciousness/agency/bounded-agency-and-reflective-freedom.pdf).

## 1. Abstracting causal models {#ref-1}

Sander Beckers and Joseph Y. Halpern. *Abstracting causal models.* Proceedings of the AAAI Conference on Artificial Intelligence, 33(1):2678–2685, 2019. [doi:10.1609/aaai.v33i01.33012678](https://doi.org/10.1609/aaai.v33i01.33012678). [Article](https://ojs.aaai.org/index.php/AAAI/article/view/4117).

## 2. Certified self-modifying code {#ref-2}

Hongxu Cai, Zhong Shao, and Alexander Vaynberg. *Certified self-modifying code.* Proceedings of the 28th ACM SIGPLAN Conference on Programming Language Design and Implementation, pp. 66–77. ACM, 2007. [doi:10.1145/1250734.1250743](https://doi.org/10.1145/1250734.1250743). [Author page and extended version](https://flint.cs.yale.edu/shao/papers/smc.html). Extended version: Yale Technical Report YALEU/DCS/TR-1379.

## 3. Games with imperfect information {#ref-3}

Krishnendu Chatterjee, Laurent Doyen, Thomas A. Henzinger, and Jean-François Raskin. *Algorithms for omega-regular games with imperfect information.* Logical Methods in Computer Science, 3(3), article 4, 2007. [doi:10.2168/LMCS-3(3:4)2007](https://doi.org/10.2168/LMCS-3(3:4)2007). [Article](https://lmcs.episciences.org/1094).

## 4. Self-modification of policy and utility {#ref-4}

Tom Everitt, Daniel Filan, Mayank Daswani, and Marcus Hutter. *Self-modification of policy and utility function in rational agents.* In Bas Steunebrink, Pei Wang, and Ben Goertzel, editors, Artificial General Intelligence, Lecture Notes in Computer Science 9782, pp. 1–11. Springer, 2016. [doi:10.1007/978-3-319-41649-6_1](https://doi.org/10.1007/978-3-319-41649-6_1). [arXiv:1605.03142](https://arxiv.org/abs/1605.03142).

## 5. Responsibility and manipulation {#ref-5}

John Martin Fischer. *Responsibility and manipulation.* The Journal of Ethics, 8(2):145–177, 2004. [doi:10.1023/B:JOET.0000018773.97209.84](https://doi.org/10.1023/B:JOET.0000018773.97209.84). [Author PDF](https://andrewmbailey.com/jmf/Responsibility_and_Manipulation.pdf).

## 6. Responsibility and control {#ref-6}

John Martin Fischer and Mark Ravizza. *Responsibility and Control: A Theory of Moral Responsibility.* Cambridge University Press, 1998. [doi:10.1017/CBO9780511814594](https://doi.org/10.1017/CBO9780511814594). [Publisher](https://www.cambridge.org/core/books/responsibility-and-control/54D0EB8AEDEF4D5F4930D691EC214E01).

## 7. Sequential testing under deadlines {#ref-7}

Peter Frazier and Angela J. Yu. *Sequential hypothesis testing under stochastic deadlines.* Advances in Neural Information Processing Systems, volume 20, 2007. [Proceedings](https://proceedings.neurips.cc/paper/2007/hash/9c82c7143c102b71c593d98d96093fde-Abstract.html).

## 8. Adaptive submodularity {#ref-8}

Daniel Golovin and Andreas Krause. *Adaptive submodularity: Theory and applications in active learning and stochastic optimization.* Journal of Artificial Intelligence Research, 42:427–486, 2011. [doi:10.1613/jair.3278](https://doi.org/10.1613/jair.3278). [arXiv:1003.3967](https://arxiv.org/abs/1003.3967). Corrected author version: v5, 2017.

## 9. Transitive factorisations {#ref-9}

I. P. Goulden and D. M. Jackson. *Transitive factorisations into transpositions and holomorphic mappings on the sphere.* Proceedings of the American Mathematical Society, 125(1):51–60, 1997. [Author PDF](https://uwaterloo.ca/math/sites/default/files/uploads/documents/gjpams1997.pdf).

## 10. Smooth simulation of computation {#ref-10}

Daniel S. Graça, Manuel L. Campagnolo, and Jorge Buescu. *Robust simulations of Turing machines with analytic maps and flows.* New Computational Paradigms, Lecture Notes in Computer Science 3526, pp. 169–179. Springer, 2005. [doi:10.1007/11494645_21](https://doi.org/10.1007/11494645_21). [Author PDF](https://sqigmath.tecnico.ulisboa.pt/pub/GracaDS/05-GCB-stable.pdf).

## 11. Selecting computations {#ref-11}

Nicholas Hay, Stuart Russell, David Tolpin, and Solomon Eyal Shimony. *Selecting computations: Theory and applications.* Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, pp. 346–355, 2012. [Proceedings PDF](https://www.auai.org/uai2012/papers/123.pdf).

## 12. Adaptivity gaps in Boolean evaluation {#ref-12}

Lisa Hellerstein, Devorah Kletenik, Naifeng Liu, and R. Teal Witter. *Adaptivity gaps for the stochastic boolean function evaluation problem.* arXiv:2208.03810, version 1, 2022. [Preprint](https://arxiv.org/abs/2208.03810).

## 13. Discovering agents {#ref-13}

Zachary Kenton, Ramana Kumar, Sebastian Farquhar, Jonathan Richens, Matt MacDermott, and Tom Everitt. *Discovering agents.* Artificial Intelligence, 322:103963, 2023. [doi:10.1016/j.artint.2023.103963](https://doi.org/10.1016/j.artint.2023.103963). [Author PDF](https://sebastianfarquhar.com/assets/papers/kentonDiscovering2023.pdf).

## 14. Can AI systems have free will? {#ref-14}

Christian List. *Can AI systems have free will?* Synthese, 206:115, 2025. [doi:10.1007/s11229-025-05209-x](https://doi.org/10.1007/s11229-025-05209-x).

## 15. Unsupervised reliability calibration {#ref-15}

Yao Ma, Alex Olshevsky, Csaba Szepesvari, and Venkatesh Saligrama. *Gradient descent for sparse rank-one matrix completion for crowd-sourced aggregation of sparsely interacting workers.* Journal of Machine Learning Research, 21(133):1–36, 2020. [Article](https://jmlr.org/papers/v21/19-359.html).

## 16. Chance, choice and control {#ref-16}

Henry D. Potter and Kevin J. Mitchell. *Chance, choice, and control: free will in an indeterministic universe.* Synthese, 207:209, 2026. [doi:10.1007/s11229-026-05570-5](https://doi.org/10.1007/s11229-026-05570-5).

## 17. General agents need world models {#ref-17}

Jonathan Richens, Tom Everitt, and David Abel. *General agents need world models.* Proceedings of the 42nd International Conference on Machine Learning, Proceedings of Machine Learning Research 267, pp. 51659–51687. PMLR, 2025. [Proceedings](https://proceedings.mlr.press/v267/richens25a.html).

## 18. Relational boundaries and awareness localization {#ref-18}

Jeremy Rodgers. *Relational boundaries and awareness localization: Robustness, composition, and identification limits.* Zenodo, 2026. Preprint, version 1.0, 29 September 2026. [Full website treatment](/consciousness/research/paper-2).

## 19. Shadow Theory and Consciousness {#ref-19}

Jeremy Rodgers. *Shadow theory and consciousness: Awareness, perspectival realization, and the source-to-experience problem.* Zenodo, 2026. SPC-2, version 2, publication edition, 20 September 2026. [Full website treatment](/consciousness/monograph).

## 20. Learning effective interfaces {#ref-20}

Jeremy Rodgers. *Learning effective interfaces from opaque stochastic systems: Capacity, selection, and validation limits.* Zenodo, 2026. Revised preprint, version 2, 29 September 2026. [Full website treatment](/consciousness/research/paper-3).

## 21. Identifying binary realizations {#ref-21}

Jeremy Rodgers. *Identifying binary realizations from intervention laws: Certificates, recoding obstructions, and a bounded SPC-2/IIT comparison.* Zenodo, 2026. Preprint, version 1.1-RC1, 30 September 2026. [Full website treatment](/consciousness/research/paper-4).

## 22. Causal consistency {#ref-22}

Paul K. Rubenstein, Sebastian Weichwald, Stephan Bongers, Joris M. Mooij, Dominik Janzing, Moritz Grosse-Wentrup, and Bernhard Schölkopf. *Causal consistency of structural equation models.* Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017. [arXiv:1707.00819](https://arxiv.org/abs/1707.00819).

## 23. Risk-aware partially observed planning {#ref-23}

Pedro Santana, Sylvie Thiébaux, and Brian Williams. *RAO\*: An algorithm for chance-constrained POMDP's.* Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, pp. 3308–3314. AAAI Press, 2016. [doi:10.1609/aaai.v30i1.10423](https://doi.org/10.1609/aaai.v30i1.10423). [Article](https://ojs.aaai.org/index.php/AAAI/article/view/10423).

## 24. Gödel machines {#ref-24}

Jürgen Schmidhuber. *Gödel machines: Fully self-referential optimal universal self-improvers.* In Ben Goertzel and Cassio Pennachin, editors, Artificial General Intelligence, Cognitive Technologies, pp. 199–226. Springer, 2007. [doi:10.1007/978-3-540-68677-4_7](https://doi.org/10.1007/978-3-540-68677-4_7). [Author page](https://people.idsia.ch/~juergen/goedelmachine.html).