Skip to content

References

Every source the documentation cites, plus the ones behind decisions recorded in DECISIONS.md and the research notes. Entries appear here whether or not a page cites them, so the list doubles as the bibliography for the programme's write-ups.

  1. Rafal Bogacz. A tutorial on the free-energy framework for modelling perception and learning. Journal of Mathematical Psychology, 76:198–211, 2017. URL: https://doi.org/10.1016/j.jmp.2015.11.003, doi:10.1016/j.jmp.2015.11.003. ↩

  2. Christopher L. Buckley, Chang Sub Kim, Simon McGregor, and Anil K. Seth. The free energy principle for action and perception: a mathematical review. Journal of Mathematical Psychology, 81:55–79, 2017. URL: https://doi.org/10.1016/j.jmp.2017.09.004, doi:10.1016/j.jmp.2017.09.004. ↩

  3. Lancelot Da Costa, Thomas Parr, Noor Sajid, Sebastijan Veselic, Victorita Neacsu, and Karl Friston. Active inference on discrete state-spaces: a synthesis. Journal of Mathematical Psychology, 99:102447, 2020. URL: https://doi.org/10.1016/j.jmp.2020.102447, doi:10.1016/j.jmp.2020.102447. ↩

  4. Ryan Smith, Karl J. Friston, and Christopher J. Whyte. A step-by-step tutorial on active inference and its application to empirical data. Journal of Mathematical Psychology, 107:102632, 2022. URL: https://doi.org/10.1016/j.jmp.2021.102632, doi:10.1016/j.jmp.2021.102632. ↩

  5. Conor Heins, Beren Millidge, Daphne Demekas, Brennan Klein, Karl Friston, Iain D. Couzin, and Alexander Tschantz. pymdp: a Python library for active inference in discrete state spaces. Journal of Open Source Software, 7(73):4098, 2022. URL: https://doi.org/10.21105/joss.04098, doi:10.21105/joss.04098. ↩

  6. Dmitry Bagaev, Albert Podusenko, and Bert de Vries. RxInfer: a Julia package for reactive real-time Bayesian inference. Journal of Open Source Software, 8(84):5161, 2023. URL: https://doi.org/10.21105/joss.05161, doi:10.21105/joss.05161. ↩

  7. Karl Friston, Francesco Rigoli, Dimitri Ognibene, Christoph Mathys, Thomas Fitzgerald, and Giovanni Pezzulo. Active inference and epistemic value. Cognitive Neuroscience, 6(4):187–214, 2015. URL: https://doi.org/10.1080/17588928.2015.1020053, doi:10.1080/17588928.2015.1020053. ↩

  8. Magnus T. Koudahl, Wouter M. Kouw, and Bert de Vries. On epistemics in expected free energy for linear Gaussian state space models. Entropy, 23(12):1565, 2021. URL: https://doi.org/10.3390/e23121565, doi:10.3390/e23121565. ↩

  9. Daniel Corva. State-dependent observation noise reintroduces epistemic value in linear-Gaussian active inference. arXiv preprint arXiv:2607.20306, 2026. URL: https://arxiv.org/abs/2607.20306, arXiv:2607.20306, doi:10.48550/arXiv.2607.20306. ↩

  10. Henry H. Mattingly, Keita Kamino, Benjamin B. Machta, and Thierry Emonet. Escherichia coli chemotaxis is information limited. Nature Physics, 17(12):1426–1431, 2021. URL: https://doi.org/10.1038/s41567-021-01380-3, doi:10.1038/s41567-021-01380-3. ↩

  11. Henry H. Mattingly, Keita Kamino, Jude Ong, Rafaela Kottou, Thierry Emonet, and Benjamin B. Machta. Escherichia coli chemosensing accuracy is not limited by stochastic molecule arrivals. Nature Physics, 22(1):123–130, 2026. URL: https://doi.org/10.1038/s41567-025-03111-4, doi:10.1038/s41567-025-03111-4. ↩

  12. Ganhui Lan and Yuhai Tu. Information processing in bacteria: memory, computation, and statistical physics: a key issues review. Reports on Progress in Physics, 79(5):052601, 2016. URL: https://doi.org/10.1088/0034-4885/79/5/052601, doi:10.1088/0034-4885/79/5/052601. ↩

  13. Sharath Sathish, Mahmoud Khader, Abdulnaser Sayma, and Sunil Shah. Centrifugal compressor design and surge simulation for active inference based control. In Proceedings of the ASME Turbo Expo 2024, volume 9, V009T19A011. London, United Kingdom, 2024. URL: https://doi.org/10.1115/GT2024-124905, doi:10.1115/GT2024-124905. ↩

  14. E. M. Greitzer. Surge and rotating stall in axial flow compressors—Part I: theoretical compression system model. Journal of Engineering for Power, 98(2):190–198, 1976. URL: https://doi.org/10.1115/1.3446138, doi:10.1115/1.3446138. ↩

  15. International Organization for Standardization. Measurement of fluid flow by means of pressure differential devices inserted in circular cross-section conduits running full — part 1: general principles and requirements. Technical Report ISO 5167-1:2022, ISO, 2022. URL: https://www.iso.org/standard/79179.html. ↩

  16. International Organization for Standardization. Measurement of fluid flow by means of pressure differential devices inserted in circular cross-section conduits running full — part 2: orifice plates. Technical Report ISO 5167-2:2022, ISO, 2022. URL: https://www.iso.org/standard/79180.html. ↩

  17. Davide Spinello and Daniel J. Stilwell. Nonlinear estimation with state-dependent Gaussian observation noise. IEEE Transactions on Automatic Control, 55(6):1358–1366, 2010. URL: https://doi.org/10.1109/TAC.2010.2042006, doi:10.1109/TAC.2010.2042006. ↩

  18. Bradley M. Bell and Frederick W. Cathey. The iterated Kalman filter update as a Gauss-Newton method. IEEE Transactions on Automatic Control, 38(2):294–297, 1993. URL: https://doi.org/10.1109/9.250476, doi:10.1109/9.250476. ↩