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 Supplementary essays identify their own dependencies and do not assign the published paper credit for additional unpublished results.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. Read the supplied PDF.

1. Abstracting causal models

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. Article.

2. Certified self-modifying code

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. Author page and extended version. Extended version: Yale Technical Report YALEU/DCS/TR-1379.

3. Games with imperfect information

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. Article.

4. Self-modification of policy and utility

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. arXiv:1605.03142.

5. Responsibility and manipulation

John Martin Fischer. Responsibility and manipulation. The Journal of Ethics, 8(2):145–177, 2004. doi:10.1023/B:JOET.0000018773.97209.84. Author PDF.

6. Responsibility and control

John Martin Fischer and Mark Ravizza. Responsibility and Control: A Theory of Moral Responsibility. Cambridge University Press, 1998. doi:10.1017/CBO9780511814594. Publisher.

7. Sequential testing under deadlines

Peter Frazier and Angela J. Yu. Sequential hypothesis testing under stochastic deadlines. Advances in Neural Information Processing Systems, volume 20, 2007. Proceedings.

8. Adaptive submodularity

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. arXiv:1003.3967. Corrected author version: v5, 2017.

9. Transitive factorisations

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.

10. Smooth simulation of computation

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. Author PDF.

11. Selecting computations

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.

12. Adaptivity gaps in Boolean evaluation

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.

13. Discovering agents

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. Author PDF.

14. Can AI systems have free will?

Christian List. Can AI systems have free will? Synthese, 206:115, 2025. doi:10.1007/s11229-025-05209-x.

15. Unsupervised reliability calibration

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.

16. Chance, choice and control

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.

17. General agents need world models

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.

18. Relational boundaries and awareness localization

Jeremy Rodgers. Relational boundaries and awareness localization: Robustness, composition, and identification limits. Zenodo, 2026. Preprint, version 1.0, 29 September 2026. Full website treatment.

19. Shadow Theory and Consciousness

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.

20. Learning effective interfaces

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.

21. Identifying binary realizations

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.

22. Causal consistency

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.

23. Risk-aware partially observed planning

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. Article.

24. Gödel machines

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. Author page.