mirror of
https://github.com/BerenMillidge/FEP_Active_Inference_Papers.git
synced 2026-06-17 02:00:27 +00:00
Compare commits
No commits in common. "main" and "add-philosophy-papers" have entirely different histories.
main
...
add-philos
3 changed files with 118 additions and 256 deletions
185
README.md
185
README.md
|
|
@ -17,105 +17,92 @@ If you are just starting out, I reccomend reading all the papers in the 'Survey'
|
|||
- [Information Geometry](https://github.com/BerenMillidge/FEP_Active_Inference_Papers/blob/master/README.md#information-geometry)
|
||||
|
||||
## Surveys
|
||||
- [**What does the free energy principle tell us about the brain?**](https://arxiv.org/abs/1901.07945) , (2019) by Samuel J Gershman [[bib]](bibtex.bib#L1-L8)
|
||||
- [**What does the free energy principle tell us about the brain?**](https://arxiv.org/abs/1901.07945) , (2019) by *Gershman, Samuel J* [[bib]](bibtex.bib#L1-L8)
|
||||
|
||||
*This provides a great high level introduction to the basic ideas and intuitions of the FEP, with a small amount of crucial mathematical background.*
|
||||
- [**The free-energy principle: a unified brain theory?**](https://www.uab.edu/medicine/cinl/images/KFriston_FreeEnergy_BrainTheory.pdf) , (2010) by Karl Friston [[bib]](bibtex.bib#L11-L22)
|
||||
- [**The free-energy principle: a unified brain theory?**](https://www.uab.edu/medicine/cinl/images/KFriston_FreeEnergy_BrainTheory.pdf) , (2010) by *Friston, Karl* [[bib]](bibtex.bib#L11-L22)
|
||||
|
||||
*This provides a great overview for the initial intuitions behind the FEP and its application to the brain.*
|
||||
- [**A tutorial on the free-energy framework for modelling perception and learning**](https://www.sciencedirect.com/science/article/pii/S0022249615000759) , (2017) by Rafal Bogacz [[bib]](bibtex.bib#L43-L53)
|
||||
- [**A tutorial on the free-energy framework for modelling perception and learning**](https://www.sciencedirect.com/science/article/pii/S0022249615000759) , (2017) by *Bogacz, Rafal* [[bib]](bibtex.bib#L27-L37)
|
||||
|
||||
*This is a great review which introduces the basics of predictive coding and the FEP, including the maths and contains MATLAB sample code. If you want to start seriously diving into the maths, I would start here.*
|
||||
- [**The free energy principle for action and perception: A mathematical review**](https://www.sciencedirect.com/science/article/pii/S0022249617300962) , (2017) by Christopher L Buckley and Chang Sub Kim and Simon McGregor and Anil K Seth [[bib]](bibtex.bib#L57-L67)
|
||||
- [**The free energy principle for action and perception: A mathematical review**](https://www.sciencedirect.com/science/article/pii/S0022249617300962) , (2017) by *Buckley, Christopher L, Kim, Chang Sub, McGregor, Simon and Seth, Anil K* [[bib]](bibtex.bib#L41-L51)
|
||||
|
||||
*This is a fantastic review which presents a complete walkthrough of the mathematical basis of the Free Energy Principle and Variational Inference, and derives predictive coding and (continuous time and state) active inference. I would reccomend reading this after Bogacz' tutorial (although be prepared -- it is a long and serious read)*
|
||||
- [**A Step-by-Step Tutorial on Active Inference and its Application to Empirical Data**](https://psyarxiv.com/b4jm6/) , (2021) by Ryan Smith and Karl Friston and Christopher Whyte [[bib]](bibtex.bib#L70-L77)
|
||||
|
||||
*A detailed and clear walkthrough of discrete-state-space active inference, including detailed MATLAB code for a sample implementation.*
|
||||
|
||||
## Classics
|
||||
- [**A free energy principle for a particular physics**](https://arxiv.org/pdf/1906.10184.pdf) , (2019) by Karl Friston [[bib]](bibtex.bib#L81-L88)
|
||||
- [**A free energy principle for a particular physics**](https://arxiv.org/pdf/1906.10184.pdf) , (2019) by *Friston, Karl* [[bib]](bibtex.bib#L55-L62)
|
||||
|
||||
*This is Karl's magisterial monograph, and contains the most comprehensive description of the FEP to date*
|
||||
- [**A free energy principle for the brain**](https://www.sciencedirect.com/science/article/pii/S092842570600060X?casa_token=rPwSn8wQvEkAAAAA:5QeLri0QzrjAC8QYtNljoqjn0nZzRJIoBso67Uw3eY9VSFdUqcIm4mkqPBNZCwYQM8PM_VdkFfE) , (2006) by Karl Friston and James Kilner and Lee Harrison [[bib]](bibtex.bib#L92-L103)
|
||||
- [**A free energy principle for the brain**](https://www.sciencedirect.com/science/article/pii/S092842570600060X?casa_token=rPwSn8wQvEkAAAAA:5QeLri0QzrjAC8QYtNljoqjn0nZzRJIoBso67Uw3eY9VSFdUqcIm4mkqPBNZCwYQM8PM_VdkFfE) , (2006) by *Friston, Karl, Kilner, James and Harrison, Lee* [[bib]](bibtex.bib#L66-L77)
|
||||
|
||||
*Perhaps the earliest paper describing the FEP. Provides a great description of the fundamental intuitions behind the theory (in needs of living systems to reduce their internal entropy to keep conditions within homeostatic bounds)*
|
||||
- [**A theory of cortical responses**](https://royalsocietypublishing.org/doi/abs/10.1098/rstb.2005.1622?casa_token=9zU-Epc4Iw4AAAAA%3AmYQq9buUvH2tb1xtL8VXFp0oHtJVGZ_4MSymueoSBUreJAhsqEOB3D-fXJnSqMnbTYP3VBo0BxwHWYE) , (2005) by Karl Friston [[bib]](bibtex.bib#L106-L117)
|
||||
- [**A theory of cortical responses**](https://royalsocietypublishing.org/doi/abs/10.1098/rstb.2005.1622?casa_token=9zU-Epc4Iw4AAAAA%3AmYQq9buUvH2tb1xtL8VXFp0oHtJVGZ_4MSymueoSBUreJAhsqEOB3D-fXJnSqMnbTYP3VBo0BxwHWYE) , (2005) by *Friston, Karl* [[bib]](bibtex.bib#L80-L91)
|
||||
|
||||
*An early but complete description of predictive coding as an application of the FEP and variational inference under Gaussian and Laplace assumptions. Also surprisingly readable. This is core reading on predictive coding and the FEP*
|
||||
- [**Learning and inference in the brain**](https://www.sciencedirect.com/science/article/pii/S0893608003002454?casa_token=Z-HR_To6rxwAAAAA:88ducipot59VHoRHJu1Ej6Kz5oLn-RMooUV9rR1fnkH50D5aNvLNENIF2XBa_3tZ0izMX5U2ED8) , (2003) by Karl Friston [[bib]](bibtex.bib#L119-L130)
|
||||
- [**Reinforcement learning or active inference?**](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0006421) , (2009) by Karl J Friston and Jean Daunizeau and Stefan J Kiebel [[bib]](bibtex.bib#L131-L142)
|
||||
- [**Learning and inference in the brain**](https://www.sciencedirect.com/science/article/pii/S0893608003002454?casa_token=Z-HR_To6rxwAAAAA:88ducipot59VHoRHJu1Ej6Kz5oLn-RMooUV9rR1fnkH50D5aNvLNENIF2XBa_3tZ0izMX5U2ED8) , (2003) by *Friston, Karl* [[bib]](bibtex.bib#L93-L104)
|
||||
- [**Reinforcement learning or active inference?**](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0006421) , (2009) by *Friston, Karl J, Daunizeau, Jean and Kiebel, Stefan J* [[bib]](bibtex.bib#L105-L116)
|
||||
|
||||
*The earliest paper (I think) on active inference. Introduces the motivation behind the continuous state and time formulation of active inference. Shows how predictive coding can be used to learn actions as well as observations (by treating them the same)*
|
||||
- [**Action understanding and active inference**](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3491875/) , (2011) by Karl Friston and J{\'e}r{\'e}mie Mattout and James Kilner [[bib]](bibtex.bib#L145-L156)
|
||||
- [**Action understanding and active inference**](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3491875/) , (2011) by *Friston, Karl, Mattout, J{\'e}r{\'e}mie and Kilner, James* [[bib]](bibtex.bib#L119-L130)
|
||||
|
||||
*Goes deep into the neuroscientific intuitions behind why you might want to think about action as a predicted observation and not a latent variable for biological brains. Presents Karl's view that action happens primarily at the periphery through simple 'reflex arcs' while all the real work is done by the generative models generating predictions.*
|
||||
- [**A free energy principle for biological systems**](https://www.mdpi.com/1099-4300/14/11/2100) , (2012) by Friston Karl [[bib]](bibtex.bib#L158-L169)
|
||||
- [**Of woodlice and men**](https://www.aliusresearch.org/uploads/9/1/6/0/91600416/alius_bulletin_n%C2%B02__2018_.pdf#page=27) , (2018) by Martin Fortier and Daniel A Friedman [[bib]](bibtex.bib#L170-L178)
|
||||
- [**A free energy principle for biological systems**](https://www.mdpi.com/1099-4300/14/11/2100) , (2012) by *Karl, Friston* [[bib]](bibtex.bib#L132-L143)
|
||||
- [**Of woodlice and men**](https://www.aliusresearch.org/uploads/9/1/6/0/91600416/alius_bulletin_n%C2%B02__2018_.pdf#page=27) , (2018) by *Fortier, Martin and Friedman, Daniel A* [[bib]](bibtex.bib#L144-L152)
|
||||
|
||||
*A great interview with Karl. Goes into a lot of his personal motivations underlying his work on the FEP. I would recommend this perhaps as an initial place to start out if you know nothing of the FEP to grasp the underlying motivations of *what* it is trying to explain.*
|
||||
- [**The history of the future of the Bayesian brain**](https://www.sciencedirect.com/science/article/pii/S1053811911011657) , (2012) by Karl Friston [[bib]](bibtex.bib#L180-L191)
|
||||
- [**Free energy, value, and attractors**](https://www.hindawi.com/journals/cmmm/2012/937860/) , (2012) by Karl Friston and Ping Ao [[bib]](bibtex.bib#L192-L201)
|
||||
- [**The history of the future of the Bayesian brain**](https://www.sciencedirect.com/science/article/pii/S1053811911011657) , (2012) by *Friston, Karl* [[bib]](bibtex.bib#L154-L165)
|
||||
- [**Free energy, value, and attractors**](https://www.hindawi.com/journals/cmmm/2012/937860/) , (2012) by *Friston, Karl and Ao, Ping* [[bib]](bibtex.bib#L166-L175)
|
||||
|
||||
*Mathematical paper by Karl and Ping Ao which begins fleshing out formally the notion of desires as attractors*
|
||||
- [**Attention, uncertainty, and free-energy**](https://www.frontiersin.org/articles/10.3389/fnhum.2010.00215/full) , (2010) by Harriet Feldman and Karl Friston [[bib]](bibtex.bib#L203-L213)
|
||||
- [**Attention, uncertainty, and free-energy**](https://www.frontiersin.org/articles/10.3389/fnhum.2010.00215/full) , (2010) by *Feldman, Harriet and Friston, Karl* [[bib]](bibtex.bib#L177-L187)
|
||||
|
||||
*Makes a conjectured link between precision in predictive coding and attention in the brain.*
|
||||
- [**Hierarchical models in the brain**](https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1000211) , (2008) by Karl Friston [[bib]](bibtex.bib#L215-L226)
|
||||
- [**Hierarchical models in the brain**](https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1000211) , (2008) by *Friston, Karl* [[bib]](bibtex.bib#L189-L200)
|
||||
|
||||
*Presents the 'full-construct' predictive coding model with both hierarchies and generalised coordinates.*
|
||||
- [**DEM: a variational treatment of dynamic systems**](https://www.sciencedirect.com/science/article/pii/S1053811908001894?casa_token=RBtljR9mpKMAAAAA:EAAQB59MLINQl8q4it_Pxnz6EbRaqvO0mMey40hdf29Qy0kKkH69qWN24jnmhcOXamuXWBqFAG4) , (2008) by Karl J Friston and N Trujillo-Barreto and Jean Daunizeau [[bib]](bibtex.bib#L228-L239)
|
||||
- [**DEM: a variational treatment of dynamic systems**](https://www.sciencedirect.com/science/article/pii/S1053811908001894?casa_token=RBtljR9mpKMAAAAA:EAAQB59MLINQl8q4it_Pxnz6EbRaqvO0mMey40hdf29Qy0kKkH69qWN24jnmhcOXamuXWBqFAG4) , (2008) by *Friston, Karl J, Trujillo-Barreto, N and Daunizeau, Jean* [[bib]](bibtex.bib#L202-L213)
|
||||
|
||||
*Extends predictive coding to generalised coordinates, and derives the necessary inference algorithms for working with them -- i.e. DEM, dynamic expectation maximisation.*
|
||||
- [**Generalised filtering**](https://www.hindawi.com/journals/mpe/2010/621670/) , (2010) by Karl Friston and Klaas Stephan and Baojuan Li and Jean Daunizeau [[bib]](bibtex.bib#L241-L250)
|
||||
- [**Surfing uncertainty: Prediction, action, and the embodied mind**](https://books.google.co.uk/books?hl=en&lr=&id=TnqECgAAQBAJ&oi=fnd&pg=PP1&dq=andy+clark+surfing+uncertainty&ots=aurm4jE3NO&sig=KxeHGJ6YJJdN9tKyr6snwDyBBKg&redir_esc=y#v=onepage&q=andy%20clark%20surfing%20uncertainty&f=false) , (2015) by Andy Clark [[bib]](bibtex.bib#L348-L355)
|
||||
- [**Variational filtering**](https://www.sciencedirect.com/science/article/pii/S1053811908002462?casa_token=bzK7h_aIzY0AAAAA:rg1CzE6vNo-cktIHO_9EAoqmR5Zpy89klEn-Wy3NAzMoR8NcWgaF5_zEzyhrRB76N5RPyCZTIlY) , (2008) by Karl J Friston [[bib]](bibtex.bib#L884-L895)
|
||||
- [**Generalised filtering**](https://www.hindawi.com/journals/mpe/2010/621670/) , (2010) by *Friston, Karl, Stephan, Klaas, Li, Baojuan and Daunizeau, Jean* [[bib]](bibtex.bib#L215-L224)
|
||||
- [**Surfing uncertainty: Prediction, action, and the embodied mind**](https://books.google.co.uk/books?hl=en&lr=&id=TnqECgAAQBAJ&oi=fnd&pg=PP1&dq=andy+clark+surfing+uncertainty&ots=aurm4jE3NO&sig=KxeHGJ6YJJdN9tKyr6snwDyBBKg&redir_esc=y#v=onepage&q=andy%20clark%20surfing%20uncertainty&f=false) , (2015) by *Clark, Andy* [[bib]](bibtex.bib#L322-L329)
|
||||
- [**Variational filtering**](https://www.sciencedirect.com/science/article/pii/S1053811908002462?casa_token=bzK7h_aIzY0AAAAA:rg1CzE6vNo-cktIHO_9EAoqmR5Zpy89klEn-Wy3NAzMoR8NcWgaF5_zEzyhrRB76N5RPyCZTIlY) , (2008) by *Friston, Karl J* [[bib]](bibtex.bib#L889-L900)
|
||||
|
||||
*Foundational treatment of variational inference for dynamical systems, as represented in generalised coordinates. Also relates variational filtering to other non-variational schemes like particle filtering and Kalman filtering.*
|
||||
- [**Action and behavior: a free-energy formulation**](https://link.springer.com/article/10.1007/s00422-010-0364-z) , (2010) by Karl J Friston and Jean Daunizeau and James Kilner and Stefan J Kiebel [[bib]](bibtex.bib#L968-L979)
|
||||
|
||||
## Philosophical Analyses
|
||||
- [**The Markov Blanket Trick: On the Scope of the Free Energy Principle and Active Inference**](http://philsci-archive.pitt.edu/18831/1/The%20Markov%20Blanket%20Trick.pdf) , (2021) by Vicente Raja and Dinesh Valluri and Edward Baggs and Anthony Chemero and Michael L Aderson [[bib]](bibtex.bib#L25-L31)
|
||||
- [**How particular is the physics of the Free Energy Principle?**](https://arxiv.org/pdf/2105.11203.pdf) , (2021) by Miguel Aguilera and Beren Millidge and Alexander Tschantz and Christopher L Buckley [[bib]](bibtex.bib#L32-L39)
|
||||
|
||||
*This paper critically analyses and deconstructs various philosophical claims about *what the FEP is saying*. Specifically, it argues that there is not necessarily a connection between the statistical notion of a Markov Blanket, and a functional notion, meaning that an actual *dynamical* separation (such as a cell membrane) does not necessarily imply a *statistical* separation in the form of a Markov Blanket and vice versa. Secondly, it demonstrates and clarifies that the FEP only makes claims about the flow of internal states *on average* over counterfactual realizations of the system, and therefore the FEP cannot describe the individual trajectories of a system in terms of free energy minimization.*
|
||||
- [**A tale of two densities: Active inference is enactive inference**](https://journals.sagepub.com/doi/pdf/10.1177/1059712319862774) , (2020) by Maxwell JD Ramstead and Michael D Kirchhoff and Karl J Friston [[bib]](bibtex.bib#L251-L262)
|
||||
- [**Answering Schr{\"o}dinger's question: A free-energy formulation**](https://www.sciencedirect.com/science/article/pii/S1571064517301409) , (2018) by Maxwell James D{\'e}sormeau Ramstead and Paul Benjamin Badcock and Karl John Friston [[bib]](bibtex.bib#L263-L273)
|
||||
- [**Thinking through other minds: A variational approach to cognition and culture**](https://royalsocietypublishing.org/doi/full/10.1098/rsif.2017.0685) , (2020) by Samuel PL Veissi{\`e}re and Axel Constant and Maxwell JD Ramstead and Karl J Friston and Laurence J Kirmayer [[bib]](bibtex.bib#L274-L283)
|
||||
- [**TTOM in action: Refining the variational approach to cognition and culture**](https://www.cambridge.org/core/journals/behavioral-and-brain-sciences/article/abs/ttom-in-action-refining-the-variational-approach-to-cognition-and-culture/ADD060A9EE6937A3104FA23290F2C519) , (2020) by Samuel PL Veissi{\`e}re and Axel Constant and Maxwell JD Ramstead and Karl J Friston and Laurence J Kirmayer [[bib]](bibtex.bib#L284-L293)
|
||||
- [**What does the free energy principle tell us about the brain?**](https://arxiv.org/abs/1901.07945) , (2019) by Samuel J Gershman [[bib]](bibtex.bib#L1-L8)
|
||||
- [**A tale of two densities: Active inference is enactive inference**](https://journals.sagepub.com/doi/pdf/10.1177/1059712319862774) , (2020) by *Ramstead, Maxwell JD, Kirchhoff, Michael D and Friston, Karl J* [[bib]](bibtex.bib#L225-L236)
|
||||
- [**Answering Schr{\"o}dinger's question: A free-energy formulation**](https://www.sciencedirect.com/science/article/pii/S1571064517301409) , (2018) by *Ramstead, Maxwell James D{\'e}sormeau, Badcock, Paul Benjamin and Friston, Karl John* [[bib]](bibtex.bib#L237-L247)
|
||||
- [**Thinking through other minds: A variational approach to cognition and culture**](https://royalsocietypublishing.org/doi/full/10.1098/rsif.2017.0685) , (2020) by *Veissi{\`e}re, Samuel PL, Constant, Axel, Ramstead, Maxwell JD, Friston, Karl J and Kirmayer, Laurence J* [[bib]](bibtex.bib#L248-L257)
|
||||
- [**TTOM in action: Refining the variational approach to cognition and culture**](https://www.cambridge.org/core/journals/behavioral-and-brain-sciences/article/abs/ttom-in-action-refining-the-variational-approach-to-cognition-and-culture/ADD060A9EE6937A3104FA23290F2C519) , (2020) by *Veissi{\`e}re, Samuel PL, Constant, Axel, Ramstead, Maxwell JD, Friston, Karl J and Kirmayer, Laurence J* [[bib]](bibtex.bib#L258-L267)
|
||||
- [**What does the free energy principle tell us about the brain?**](https://arxiv.org/abs/1901.07945) , (2019) by *Gershman, Samuel J* [[bib]](bibtex.bib#L1-L8)
|
||||
|
||||
*This provides a great high level introduction to the basic ideas and intuitions of the FEP, with a small amount of crucial mathematical background.*
|
||||
- [**The anticipating brain is not a scientist: the free-energy principle from an ecological-enactive perspective**](https://link.springer.com/article/10.1007/s11229-016-1239-1) , (2018) by Jelle Bruineberg and Julian Kiverstein and Erik Rietveld [[bib]](bibtex.bib#L302-L313)
|
||||
- [**Predictive processing and the representation wars**](https://link.springer.com/article/10.1007/s11023-017-9441-6) , (2018) by Daniel Williams [[bib]](bibtex.bib#L314-L325)
|
||||
- [**Whatever next? Predictive brains, situated agents, and the future of cognitive science**](https://www.cambridge.org/core/journals/behavioral-and-brain-sciences/article/whatever-next-predictive-brains-situated-agents-and-the-future-of-cognitive-science/33542C736E17E3D1D44E8D03BE5F4CD9) , (2013) by Andy Clark [[bib]](bibtex.bib#L326-L337)
|
||||
- [**Predictions in the eye of the beholder: an active inference account of Watt governors**](https://www.mitpressjournals.org/doi/abs/10.1162/isal_a_00288) , (2020) by Manuel Baltieri and Christopher L Buckley and Jelle Bruineberg [[bib]](bibtex.bib#L338-L347)
|
||||
- [**From allostatic agents to counterfactual cognisers: active inference, biological regulation, and the origins of cognition**](https://link.springer.com/article/10.1007/s10539-020-09746-2) , (2020) by Andrew W Corcoran and Giovanni Pezzulo and Jakob Hohwy [[bib]](bibtex.bib#L825-L836)
|
||||
- [**Interoceptive inference, emotion, and the embodied self**](https://www.sciencedirect.com/science/article/pii/S1364661313002118) , (2013) by Anil K Seth [[bib]](bibtex.bib#L837-L848)
|
||||
- [**Active interoceptive inference and the emotional brain**](https://royalsocietypublishing.org/doi/full/10.1098/rstb.2016.0007) , (2016) by Anil K Seth and Karl J Friston [[bib]](bibtex.bib#L849-L860)
|
||||
- [**The cybernetic Bayesian brain**](https://open-mind.net/papers/the-cybernetic-bayesian-brain) , (2014) by Anil K Seth [[bib]](bibtex.bib#L861-L868)
|
||||
- [**Presence, objecthood, and the phenomenology of predictive perception**](https://www.tandfonline.com/doi/full/10.1080/17588928.2015.1026888?casa_token=IA7GL_oM2VAAAAAA%3AXkJ7HbhxHcW7qCdSWyRSerOo8iZevM3x_8QV1b7C7qAvAqJMveeq4IeGRBTCCbQOCJ6Ix9p70VkKww) , (2015) by Anil K Seth [[bib]](bibtex.bib#L869-L880)
|
||||
- [**The Math is not the Territory: Navigating the Free Energy Principle**](http://philsci-archive.pitt.edu/18315/) , (2020) by Mel Andrews [[bib]](bibtex.bib#L940-L946)
|
||||
- [**The anticipating brain is not a scientist: the free-energy principle from an ecological-enactive perspective**](https://link.springer.com/article/10.1007/s11229-016-1239-1) , (2018) by *Bruineberg, Jelle, Kiverstein, Julian and Rietveld, Erik* [[bib]](bibtex.bib#L276-L287)
|
||||
- [**Predictive processing and the representation wars**](https://link.springer.com/article/10.1007/s11023-017-9441-6) , (2018) by *Williams, Daniel* [[bib]](bibtex.bib#L288-L299)
|
||||
- [**Whatever next? Predictive brains, situated agents, and the future of cognitive science**](https://www.cambridge.org/core/journals/behavioral-and-brain-sciences/article/whatever-next-predictive-brains-situated-agents-and-the-future-of-cognitive-science/33542C736E17E3D1D44E8D03BE5F4CD9) , (2013) by *Clark, Andy* [[bib]](bibtex.bib#L300-L311)
|
||||
- [**Predictions in the eye of the beholder: an active inference account of Watt governors**](https://www.mitpressjournals.org/doi/abs/10.1162/isal_a_00288) , (2020) by *Baltieri, Manuel, Buckley, Christopher L and Bruineberg, Jelle* [[bib]](bibtex.bib#L312-L321)
|
||||
- [**From allostatic agents to counterfactual cognisers: active inference, biological regulation, and the origins of cognition**](https://link.springer.com/article/10.1007/s10539-020-09746-2) , (2020) by *Corcoran, Andrew W, Pezzulo, Giovanni and Hohwy, Jakob* [[bib]](bibtex.bib#L796-L807)
|
||||
- [**Interoceptive inference, emotion, and the embodied self**](https://www.sciencedirect.com/science/article/pii/S1364661313002118) , (2013) by *Seth, Anil K* [[bib]](bibtex.bib#L808-L819)
|
||||
- [**Active interoceptive inference and the emotional brain**](https://royalsocietypublishing.org/doi/full/10.1098/rstb.2016.0007) , (2016) by *Seth, Anil K and Friston, Karl J* [[bib]](bibtex.bib#L820-L831)
|
||||
- [**The cybernetic Bayesian brain**](https://open-mind.net/papers/the-cybernetic-bayesian-brain) , (2014) by *Seth, Anil K* [[bib]](bibtex.bib#L832-L839)
|
||||
- [**Presence, objecthood, and the phenomenology of predictive perception**](https://www.tandfonline.com/doi/full/10.1080/17588928.2015.1026888?casa_token=IA7GL_oM2VAAAAAA%3AXkJ7HbhxHcW7qCdSWyRSerOo8iZevM3x_8QV1b7C7qAvAqJMveeq4IeGRBTCCbQOCJ6Ix9p70VkKww) , (2015) by *Seth, Anil K* [[bib]](bibtex.bib#L840-L851)
|
||||
- [**First principles in the life sciences: The free-energy principle, organicism, and mechanism**](https://link.springer.com/article/10.1007/s11229-018-01932-w) , (2018) by *Colombo, Matteo and Wright, Cory* [[bib]](bibtex.bib#L853-L863)
|
||||
- [**From cognitivism to autopoiesis: towards a computational framework for the embodied mind**](https://link.springer.com/article/10.1007%2Fs11229-016-1288-5) , (2018) by *Allen, Micah and Friston, Karl J* [[bib]](bibtex.bib#L864-L875)
|
||||
- [**Computational enactivism under the free energy principle**](https://link.springer.com/article/10.1007/s11229-019-02243-4) , (2019) by *Korbak, Tomasz* [[bib]](bibtex.bib#L876-L886)
|
||||
|
||||
## Self-Organisation and Markov Blankets
|
||||
- [**Life as we know it**](https://royalsocietypublishing.org/doi/full/10.1098/rsif.2013.0475) , (2013) by Karl Friston [[bib]](bibtex.bib#L357-L368)
|
||||
|
||||
*A heuristic demonstration of the concept that Karl will later refer to as 'Bayesian mechanics', this paper surveys the notion that any random dynamical systems with the right kind of coupling among its sub-systems (i.e. a Markov blanket), will naturally appear as if it's performing a kind of approximate Bayesian inference. This argument is motivated by appeal to the existence of a non-equilibrium steady-state density, to which the system's probability distribution converges over time.*
|
||||
- [**Knowing one's place: a free-energy approach to pattern regulation**](https://royalsocietypublishing.org/doi/full/10.1098/rsif.2014.1383) , (2015) by Karl Friston and Michael Levin and Biswa Sengupta and Giovanni Pezzulo [[bib]](bibtex.bib#L369-L380)
|
||||
- [**Morphogenesis as Bayesian inference: A variational approach to pattern formation and control in complex biological systems**](https://www.sciencedirect.com/science/article/pii/S1571064519300909?casa_token=IrMsxOkLhfYAAAAA:2agLQQPi8aeYTxxqotIPCyEzsHbpvOLwf_0eK5oW2Li0Gi5THHn2XRpWYfNT99M0Xy5pPD_S9CA) , (2019) by Franz Kuchling and Karl Friston and Georgi Georgiev and Michael Levin [[bib]](bibtex.bib#L381-L389)
|
||||
- [**Neural and phenotypic representation under the free-energy principle**](https://www.sciencedirect.com/science/article/pii/S0149763420306643?casa_token=16rC0ManFBUAAAAA:3mbntn5I7fObnA_Y397rvZbWrnUzkqmALD1LtS88tGrIRxbw9RQvU55XJuH-zKdBi6tPaN9faDM) , (2020) by Maxwell JD Ramstead and Casper Hesp and Alexander Tschantz and Ryan Smith and Axel Constant and Karl Friston [[bib]](bibtex.bib#L390-L398)
|
||||
- [**Parcels and particles: Markov blankets in the brain**](https://arxiv.org/abs/2007.09704) , (2020) by Karl J Friston and Erik D Fagerholm and Tahereh S Zarghami and Thomas Parr and In{\^e}s Hip{\'o}lito and Lo{\"\i}c Magrou and Adeel Razi [[bib]](bibtex.bib#L399-L406)
|
||||
- [**Markov blankets in the brain**](https://arxiv.org/abs/2006.02741) , (2020) by Ines Hipolito and Maxwell Ramstead and Laura Convertino and Anjali Bhat and Karl Friston and Thomas Parr [[bib]](bibtex.bib#L407-L414)
|
||||
- [**Modules or Mean-Fields?**](https://www.mdpi.com/1099-4300/22/5/552) , (2020) by Thomas Parr and Noor Sajid and Karl J Friston [[bib]](bibtex.bib#L416-L427)
|
||||
|
||||
*The 'free energy' response to the Fodorian notion of 'modularity' as an explanation of functional segregation, here motivated by an appeal to the stochastic dynamics of Markov-blanketed systems. Parr et al. argue that, given a particular conditional independency structure among the components that comprise a random dynamical system, one can interpret the system and its dynamics as entertaining a mean-field factorised generative model of its local environment, as opposed to appealing to philosophically or otherwise-unsatisfying notions such as 'modularity'.*
|
||||
- [**Biological self-organisation and Markov blankets**](https://www.biorxiv.org/content/10.1101/227181v1.abstract) , (2017) by Ensor Rafael Palacios and Adeel Razi and Thomas Parr and Michael Kirchhoff and Karl Friston [[bib]](bibtex.bib#L428-L437)
|
||||
- [**The Emperor’s New Markov Blankets**](http://philsci-archive.pitt.edu/18467/) , (2020) by Jelle Bruineberg and Krzysztof Dolega and Joe Dewhurst and Manuel Baltieri [[bib]](bibtex.bib#L593-L599)
|
||||
- [**Life as we know it**](https://royalsocietypublishing.org/doi/full/10.1098/rsif.2013.0475) , (2013) by *Friston, Karl* [[bib]](bibtex.bib#L330-L341)
|
||||
- [**Knowing one's place: a free-energy approach to pattern regulation**](https://royalsocietypublishing.org/doi/full/10.1098/rsif.2014.1383) , (2015) by *Friston, Karl, Levin, Michael, Sengupta, Biswa and Pezzulo, Giovanni* [[bib]](bibtex.bib#L342-L353)
|
||||
- [**Morphogenesis as Bayesian inference: A variational approach to pattern formation and control in complex biological systems**](https://www.sciencedirect.com/science/article/pii/S1571064519300909?casa_token=IrMsxOkLhfYAAAAA:2agLQQPi8aeYTxxqotIPCyEzsHbpvOLwf_0eK5oW2Li0Gi5THHn2XRpWYfNT99M0Xy5pPD_S9CA) , (2019) by *Kuchling, Franz, Friston, Karl, Georgiev, Georgi and Levin, Michael* [[bib]](bibtex.bib#L354-L362)
|
||||
- [**Neural and phenotypic representation under the free-energy principle**](https://www.sciencedirect.com/science/article/pii/S0149763420306643?casa_token=16rC0ManFBUAAAAA:3mbntn5I7fObnA_Y397rvZbWrnUzkqmALD1LtS88tGrIRxbw9RQvU55XJuH-zKdBi6tPaN9faDM) , (2020) by *Ramstead, Maxwell JD, Hesp, Casper, Tschantz, Alexander, Smith, Ryan, Constant, Axel and Friston, Karl* [[bib]](bibtex.bib#L363-L371)
|
||||
- [**Parcels and particles: Markov blankets in the brain**](https://arxiv.org/abs/2007.09704) , (2020) by *Friston, Karl J, Fagerholm, Erik D, Zarghami, Tahereh S, Parr, Thomas, Hip{\'o}lito, In{\^e}s, Magrou, Lo{\"\i}c and Razi, Adeel* [[bib]](bibtex.bib#L372-L379)
|
||||
- [**Markov blankets in the brain**](https://arxiv.org/abs/2006.02741) , (2020) by *Hipolito, Ines, Ramstead, Maxwell, Convertino, Laura, Bhat, Anjali, Friston, Karl and Parr, Thomas* [[bib]](bibtex.bib#L380-L387)
|
||||
- [**Modules or Mean-Fields?**](https://www.mdpi.com/1099-4300/22/5/552) , (2020) by *Parr, Thomas, Sajid, Noor and Friston, Karl J* [[bib]](bibtex.bib#L388-L399)
|
||||
- [**Biological self-organisation and Markov blankets**](https://www.biorxiv.org/content/10.1101/227181v1.abstract) , (2017) by *Palacios, Ensor Rafael, Razi, Adeel, Parr, Thomas, Kirchhoff, Michael and Friston, Karl* [[bib]](bibtex.bib#L400-L409)
|
||||
|
||||
## Information Geometry
|
||||
- [**Markov blankets, information geometry and stochastic thermodynamics**](https://royalsocietypublishing.org/doi/full/10.1098/rsta.2019.0159) , (2020) by Thomas Parr and Lancelot Da Costa and Karl Friston [[bib]](bibtex.bib#L439-L450)
|
||||
|
||||
*This paper gives succinct and schematic treatments of several of the main concepts explored in a Free Energy Principle for a Particular Physics, particularly those related to Bayesian mechanics and information geometry. This work importantly delineates some of the conditions required of a system, so that its internal states approximately parameterise beliefs about external states. Fluctuation theorems are also invoked to relate the probability of trajectories or sequences of states to existing concepts in the active inference world, such as information gain, risk, and ambiguity resolution.*
|
||||
- [**Markov blankets, information geometry and stochastic thermodynamics**](https://royalsocietypublishing.org/doi/full/10.1098/rsta.2019.0159) , (2020) by *Parr, Thomas, Da Costa, Lancelot and Friston, Karl* [[bib]](bibtex.bib#L410-L421)
|
||||
|
||||
|
||||
## Active Inference Outline
|
||||
|
|
@ -135,111 +122,99 @@ The task of inferring actions (requiring detailed models of future outcomes give
|
|||
- [Continuous Time Formulation](https://github.com/BerenMillidge/FEP_Active_Inference_Papers/blob/master/README.md#continuous-time-formulation)
|
||||
- [Message Passing and Free Energies](https://github.com/BerenMillidge/FEP_Active_Inference_Papers/blob/master/README.md#message-passing-and-free-energies)
|
||||
- [Active Inference for Control Theory/Robotics](https://github.com/BerenMillidge/FEP_Active_Inference_Papers/blob/master/README.md#active-inference-for-control-theory/robotics)
|
||||
- [Neuroscience and Computational Psychiatry Applications](https://github.com/BerenMillidge/FEP_Active_Inference_Papers/blob/master/README.md#neuroscience-and-computational-psychiatry-applications)
|
||||
- [Deep Active Inference](https://github.com/BerenMillidge/FEP_Active_Inference_Papers/blob/master/README.md#deep-active-inference)
|
||||
|
||||
## Surveys and Tutorials
|
||||
- [**Active inference on discrete state-spaces: a synthesis**](https://arxiv.org/abs/2001.07203) , (2020) by Lancelot Da Costa and Thomas Parr and Noor Sajid and Sebastijan Veselic and Victorita Neacsu and Karl Friston [[bib]](bibtex.bib#L451-L458)
|
||||
- [**Active inference on discrete state-spaces: a synthesis**](https://arxiv.org/abs/2001.07203) , (2020) by *Da Costa, Lancelot, Parr, Thomas, Sajid, Noor, Veselic, Sebastijan, Neacsu, Victorita and Friston, Karl* [[bib]](bibtex.bib#L422-L429)
|
||||
|
||||
*This is a great and thorough tutorial on discrete-state-space active inference. I would reccomend it to everybody new to the field.*
|
||||
|
||||
## Discrete State Space Formulation
|
||||
- [**Active inference and epistemic value**](https://www.tandfonline.com/doi/full/10.1080/17588928.2015.1020053?casa_token=IiMRlTIPAXUAAAAA%3ASvxdCeRv4yruAnjsNhletPuaWzdb8dfm-5s1YvTBaup1IgHNChHDKgCe1DY40DAvYHK6ZO4_guujAA) , (2015) by Karl Friston and Francesco Rigoli and Dimitri Ognibene and Christoph Mathys and Thomas Fitzgerald and Giovanni Pezzulo [[bib]](bibtex.bib#L460-L471)
|
||||
- [**Active inference and epistemic value**](https://www.tandfonline.com/doi/full/10.1080/17588928.2015.1020053?casa_token=IiMRlTIPAXUAAAAA%3ASvxdCeRv4yruAnjsNhletPuaWzdb8dfm-5s1YvTBaup1IgHNChHDKgCe1DY40DAvYHK6ZO4_guujAA) , (2015) by *Friston, Karl, Rigoli, Francesco, Ognibene, Dimitri, Mathys, Christoph, Fitzgerald, Thomas and Pezzulo, Giovanni* [[bib]](bibtex.bib#L431-L442)
|
||||
|
||||
*Introduces the main intuitions behind active inference, as well as the crucial epistemic foraging behaviour of the expected free energy. Illustrated on a simple T-maze task.*
|
||||
- [**Active inference and learning**](https://www.sciencedirect.com/science/article/pii/S0149763416301336) , (2016) by Karl Friston and Thomas FitzGerald and Francesco Rigoli and Philipp Schwartenbeck and Giovanni Pezzulo and others [[bib]](bibtex.bib#L473-L483)
|
||||
- [**Active inference and agency: optimal control without cost functions**](https://link.springer.com/article/10.1007/s00422-012-0512-8) , (2012) by Karl Friston and Spyridon Samothrakis and Read Montague [[bib]](bibtex.bib#L484-L495)
|
||||
- [**Active inference and learning**](https://www.sciencedirect.com/science/article/pii/S0149763416301336) , (2016) by *Friston, Karl, FitzGerald, Thomas, Rigoli, Francesco, Schwartenbeck, Philipp, Pezzulo, Giovanni and others* [[bib]](bibtex.bib#L444-L454)
|
||||
- [**Active inference and agency: optimal control without cost functions**](https://link.springer.com/article/10.1007/s00422-012-0512-8) , (2012) by *Friston, Karl, Samothrakis, Spyridon and Montague, Read* [[bib]](bibtex.bib#L455-L466)
|
||||
|
||||
*The first (I think) discrete-state-space paper on active inference. Notable for using the standard variational free energy as objective function and not the expected free energy. Describes some of the intuitions behind active inference.*
|
||||
- [**Active inference: a process theory**](https://www.mitpressjournals.org/doi/full/10.1162/NECO_a_00912) , (2017) by Karl Friston and Thomas FitzGerald and Francesco Rigoli and Philipp Schwartenbeck and Giovanni Pezzulo [[bib]](bibtex.bib#L497-L508)
|
||||
- [**Active inference: a process theory**](https://www.mitpressjournals.org/doi/full/10.1162/NECO_a_00912) , (2017) by *Friston, Karl, FitzGerald, Thomas, Rigoli, Francesco, Schwartenbeck, Philipp and Pezzulo, Giovanni* [[bib]](bibtex.bib#L468-L479)
|
||||
|
||||
*Provides a very good and thorough description of discrete-state-space active inference and ties its updates closely to neural physiology. I would reccomend this after the Da Costa introduction.*
|
||||
- [**Uncertainty, epistemics and active inference**](https://royalsocietypublishing.org/doi/full/10.1098/rsif.2017.0376) , (2017) by Thomas Parr and Karl J Friston [[bib]](bibtex.bib#L510-L521)
|
||||
- [**Deep temporal models and active inference**](https://www.sciencedirect.com/science/article/pii/S0149763416307096) , (2018) by Karl J Friston and Richard Rosch and Thomas Parr and Cathy Price and Howard Bowman [[bib]](bibtex.bib#L522-L532)
|
||||
- [**Sophisticated Inference**](https://arxiv.org/abs/2006.04120) , (2020) by Karl Friston and Lancelot Da Costa and Danijar Hafner and Casper Hesp and Thomas Parr [[bib]](bibtex.bib#L600-L607)
|
||||
- [**Uncertainty, epistemics and active inference**](https://royalsocietypublishing.org/doi/full/10.1098/rsif.2017.0376) , (2017) by *Parr, Thomas and Friston, Karl J* [[bib]](bibtex.bib#L481-L492)
|
||||
- [**Deep temporal models and active inference**](https://www.sciencedirect.com/science/article/pii/S0149763416307096) , (2018) by *Friston, Karl J, Rosch, Richard, Parr, Thomas, Price, Cathy and Bowman, Howard* [[bib]](bibtex.bib#L493-L503)
|
||||
- [**Sophisticated Inference**](https://arxiv.org/abs/2006.04120) , (2020) by *Friston, Karl, Da Costa, Lancelot, Hafner, Danijar, Hesp, Casper and Parr, Thomas* [[bib]](bibtex.bib#L571-L578)
|
||||
|
||||
*Introduces the next stage of active inference. 'Sophisticated' active inference, where agents make decisions not just on their beliefs about the future, but on how their beliefs will change in the future. Allows the simulation of real epistemic value -- i.e. act so as to change your beliefs in the future.*
|
||||
- [**Active inference: demystified and compared**](https://ui.adsabs.harvard.edu/abs/2019arXiv190910863S/abstract) , (2019) by Noor Sajid and Philip J Ball and Karl J Friston [[bib]](bibtex.bib#L609-L617)
|
||||
- [**The relationship between dynamic programming and active inference: The discrete, finite-horizon case**](https://arxiv.org/abs/2009.08111) , (2020) by Lancelot Da Costa and Noor Sajid and Thomas Parr and Karl Friston and Ryan Smith [[bib]](bibtex.bib#L618-L625)
|
||||
- [**Active inference: demystified and compared**](https://ui.adsabs.harvard.edu/abs/2019arXiv190910863S/abstract) , (2019) by *Sajid, Noor, Ball, Philip J and Friston, Karl J* [[bib]](bibtex.bib#L580-L588)
|
||||
- [**The relationship between dynamic programming and active inference: The discrete, finite-horizon case**](https://arxiv.org/abs/2009.08111) , (2020) by *Da Costa, Lancelot, Sajid, Noor, Parr, Thomas, Friston, Karl and Smith, Ryan* [[bib]](bibtex.bib#L589-L596)
|
||||
|
||||
*Discusses the relationship between active inference and dynamic programming solutions to reinforcement learning problems (i.e. Q learning, value functions etc). Shows that they are largely equivalent except with different objectives (Expected Free Energy vs Expected Discounted Reward).*
|
||||
|
||||
## Continuous Time Formulation
|
||||
- [**Reinforcement learning or active inference?**](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0006421) , (2009) by Karl J Friston and Jean Daunizeau and Stefan J Kiebel [[bib]](bibtex.bib#L131-L142)
|
||||
- [**Reinforcement learning or active inference?**](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0006421) , (2009) by *Friston, Karl J, Daunizeau, Jean and Kiebel, Stefan J* [[bib]](bibtex.bib#L105-L116)
|
||||
|
||||
*The earliest paper (I think) on active inference. Introduces the motivation behind the continuous state and time formulation of active inference. Shows how predictive coding can be used to learn actions as well as observations (by treating them the same)*
|
||||
- [**An active inference implementation of phototaxis**](https://www.mitpressjournals.org/doi/abs/10.1162/isal_a_011) , (2017) by Manuel Baltieri and Christopher L Buckley [[bib]](bibtex.bib#L704-L713)
|
||||
- [**An active inference implementation of phototaxis**](https://www.mitpressjournals.org/doi/abs/10.1162/isal_a_011) , (2017) by *Baltieri, Manuel and Buckley, Christopher L* [[bib]](bibtex.bib#L675-L684)
|
||||
|
||||
*Active inference in plants!!!*
|
||||
- [**PID control as a process of active inference with linear generative models**](https://www.mdpi.com/1099-4300/21/3/257) , (2019) by Manuel Baltieri and Christopher L Buckley [[bib]](bibtex.bib#L716-L727)
|
||||
- [**PID control as a process of active inference with linear generative models**](https://www.mdpi.com/1099-4300/21/3/257) , (2019) by *Baltieri, Manuel and Buckley, Christopher L* [[bib]](bibtex.bib#L687-L698)
|
||||
|
||||
*Active inference under a linear gaussian generative model can replicate PID, but also provide a natural method for learning the tuning coefficients (by understanding them as precisions).*
|
||||
- [**On Kalman-Bucy filters, linear quadratic control and active inference**](https://arxiv.org/abs/2005.06269) , (2020) by Manuel Baltieri and Christopher L Buckley [[bib]](bibtex.bib#L729-L736)
|
||||
- [**On Kalman-Bucy filters, linear quadratic control and active inference**](https://arxiv.org/abs/2005.06269) , (2020) by *Baltieri, Manuel and Buckley, Christopher L* [[bib]](bibtex.bib#L700-L707)
|
||||
|
||||
*A key step towards understanding how active inference relates to classical control theory methods such as Kalman Filters and LQR control.*
|
||||
- [**Application of the Free Energy Principle to Estimation and Control**](https://arxiv.org/abs/1910.09823) , (2019) by Thijs van de Laar and Ay{\c{c}}a {\"O}z{\c{c}}elikkale and Henk Wymeersch [[bib]](bibtex.bib#L746-L753)
|
||||
- [**Application of the Free Energy Principle to Estimation and Control**](https://arxiv.org/abs/1910.09823) , (2019) by *van de Laar, Thijs, {\"O}z{\c{c}}elikkale, Ay{\c{c}}a and Wymeersch, Henk* [[bib]](bibtex.bib#L717-L724)
|
||||
|
||||
*Another approach to understanding how active inference relates to and extends classical control theory methods.*
|
||||
- [**The State Space Formulation of Active Inference: Towards Brain-Inspired Robot Control**](https://repository.tudelft.nl/islandora/object/uuid:0f56c37c-d22b-478b-8a85-dca615a8f419) , (2019) by Sherin Grimbergen [[bib]](bibtex.bib#L755-L761)
|
||||
- [**The State Space Formulation of Active Inference: Towards Brain-Inspired Robot Control**](https://repository.tudelft.nl/islandora/object/uuid:0f56c37c-d22b-478b-8a85-dca615a8f419) , (2019) by *Grimbergen, Sherin* [[bib]](bibtex.bib#L726-L732)
|
||||
|
||||
*An excellent overview and fantastic piece of work on the linear time-indepenent formulation of active inference and its relation to classical control theory.*
|
||||
- [**Hierarchical active inference: A theory of motivated control**](https://www.sciencedirect.com/science/article/pii/S1364661318300226) , (2018) by Giovanni Pezzulo and Francesco Rigoli and Karl J Friston [[bib]](bibtex.bib#L813-L824)
|
||||
- [**Hierarchical active inference: A theory of motivated control**](https://www.sciencedirect.com/science/article/pii/S1364661318300226) , (2018) by *Pezzulo, Giovanni, Rigoli, Francesco and Friston, Karl J* [[bib]](bibtex.bib#L784-L795)
|
||||
|
||||
## Message Passing and Free Energies
|
||||
- [**The graphical brain: belief propagation and active inference**](https://www.mitpressjournals.org/doi/full/10.1162/NETN_a_00018) , (2017) by Karl J Friston and Thomas Parr and Bert de Vries [[bib]](bibtex.bib#L533-L544)
|
||||
- [**The graphical brain: belief propagation and active inference**](https://www.mitpressjournals.org/doi/full/10.1162/NETN_a_00018) , (2017) by *Friston, Karl J, Parr, Thomas and de Vries, Bert* [[bib]](bibtex.bib#L504-L515)
|
||||
|
||||
*Introduces the general factor-graph message passing viewpoint on active inference. Also introduces hierarchical active inference models.*
|
||||
- [**Neuronal message passing using Mean-field, Bethe, and Marginal approximations**](https://www.nature.com/articles/s41598-018-38246-3) , (2019) by Thomas Parr and Dimitrije Markovic and Stefan J Kiebel and Karl J Friston [[bib]](bibtex.bib#L546-L557)
|
||||
- [**Neuronal message passing using Mean-field, Bethe, and Marginal approximations**](https://www.nature.com/articles/s41598-018-38246-3) , (2019) by *Parr, Thomas, Markovic, Dimitrije, Kiebel, Stefan J and Friston, Karl J* [[bib]](bibtex.bib#L517-L528)
|
||||
|
||||
*Discusses in depth the different potential message passing inference algorithms which can be used to implement active inference on factor graphs.*
|
||||
- [**Active inference, belief propagation, and the bethe approximation**](https://www.mitpressjournals.org/doi/abs/10.1162/neco_a_01108) , (2018) by Sarah Schw{\"o}bel and Stefan Kiebel and Dimitrije Markovi{\'c} [[bib]](bibtex.bib#L559-L570)
|
||||
- [**Active inference, belief propagation, and the bethe approximation**](https://www.mitpressjournals.org/doi/abs/10.1162/neco_a_01108) , (2018) by *Schw{\"o}bel, Sarah, Kiebel, Stefan and Markovi{\'c}, Dimitrije* [[bib]](bibtex.bib#L530-L541)
|
||||
|
||||
*Introduces the Bethe free energy, as a result of making the Bethe approximation instead of the mean-field variational assumption to derive the message passing algorithms.*
|
||||
- [**Generalised free energy and active inference**](https://link.springer.com/article/10.1007/s00422-019-00805-w) , (2019) by Thomas Parr and Karl J Friston [[bib]](bibtex.bib#L572-L583)
|
||||
- [**Whence the Expected Free Energy?**](https://arxiv.org/abs/2004.08128) , (2020) by Beren Millidge and Alexander Tschantz and Christopher L Buckley [[bib]](bibtex.bib#L584-L591)
|
||||
- [**Generalised free energy and active inference**](https://link.springer.com/article/10.1007/s00422-019-00805-w) , (2019) by *Parr, Thomas and Friston, Karl J* [[bib]](bibtex.bib#L543-L554)
|
||||
- [**Whence the Expected Free Energy?**](https://arxiv.org/abs/2004.08128) , (2020) by *Millidge, Beren, Tschantz, Alexander and Buckley, Christopher L* [[bib]](bibtex.bib#L555-L562)
|
||||
|
||||
*Discusses whether we can derive the expected free energy objective function on principled ground from the FEP, and discusses different potential objective functions for active inference.*
|
||||
- [**On the Relationship Between Active Inference and Control as Inference**](https://arxiv.org/abs/2006.12964) , (2020) by Beren Millidge and Alexander Tschantz and Anil K Seth and Christopher L Buckley [[bib]](bibtex.bib#L639-L646)
|
||||
- [**On the Relationship Between Active Inference and Control as Inference**](https://arxiv.org/abs/2006.12964) , (2020) by *Millidge, Beren, Tschantz, Alexander, Seth, Anil K and Buckley, Christopher L* [[bib]](bibtex.bib#L610-L617)
|
||||
|
||||
*Discusses the relationship between Active Inference and Control as Inference, a variational framework for understanding action selection which has emerged from RL.*
|
||||
|
||||
## Active Inference for Control Theory/Robotics
|
||||
- [**Active inference and robot control: a case study**](https://royalsocietypublishing.org/doi/full/10.1098/rsif.2016.0616) , (2016) by L{\'e}o Pio-Lopez and Ange Nizard and Karl Friston and Giovanni Pezzulo [[bib]](bibtex.bib#L763-L774)
|
||||
- [**Active inference body perception and action for humanoid robots**](https://arxiv.org/abs/1906.03022) , (2019) by Guillermo Oliver and Pablo Lanillos and Gordon Cheng [[bib]](bibtex.bib#L775-L782)
|
||||
- [**End-to-end pixel-based deep active inference for body perception and action**](https://arxiv.org/abs/2001.05847) , (2019) by Cansu Sancaktar and Pablo Lanillos [[bib]](bibtex.bib#L783-L790)
|
||||
- [**Active inference for robot control: A factor graph approach**](https://pdfs.semanticscholar.org/e177/b21b0a7f43ad3969ceb42bd8f1d912ea8d43.pdf) , (2019) by Mees Vanderbroeck and Mohamed Baioumy and Daan van der Lans and Rens de Rooij and Tiis van der Werf [[bib]](bibtex.bib#L791-L800)
|
||||
- [**A novel adaptive controller for robot manipulators based on active inference**](https://ieeexplore.ieee.org/abstract/document/9000729/?casa_token=OBL93SqhogUAAAAA:6w99NtC-Fk7P0tIiXx6QmTNsWnPS-GKK0OtsJEz-HWgniXwpY0Rtue_qlc5Fe9HQ2vj0ropx7hM) , (2020) by Corrado Pezzato and Riccardo Ferrari and Carlos Hern{\'a}ndez Corbato [[bib]](bibtex.bib#L801-L812)
|
||||
- [**Adaptive robot body learning and estimation through predictive coding**](https://ieeexplore.ieee.org/document/8593684/) , (2018) by Pablo Lanillos and Gordon Cheng [[bib]](bibtex.bib#L958-L967)
|
||||
|
||||
## Neuroscience and Computational Psychiatry Applications
|
||||
- [**Recent advances in the application of predictive coding and active inference models within clinical neuroscience**](https://onlinelibrary.wiley.com/doi/abs/10.1111/pcn.13138) , (2020) by Ryan Smith and Paul Badcock and Karl J Friston [[bib]](bibtex.bib#L897-L905)
|
||||
|
||||
*A comprehensive review of neuroscientific and computational psychiatry applications of the FEP and Active Inference.*
|
||||
- [**The Predictive Global Neuronal Workspace: A Formal Active Inference Model of Visual Consciousness**](https://www.sciencedirect.com/science/article/pii/S0301008220301738) , (2020) by Christopher J Whyte and Ryan Smith [[bib]](bibtex.bib#L908-L916)
|
||||
- [**Neurocomputational mechanisms underlying emotional awareness: insights afforded by deep active inference and their potential clinical relevance**](https://www.sciencedirect.com/science/article/pii/S014976341930541X?casa_token=c1UILIbIsKYAAAAA:tQbclbvyieFsSPf_oqulTP8Manv6fU6CeI1iHGZe5Iq4TryLR4pGRjK0Y7RD4gZCfjJo02uWyvw) , (2019) by Ryan Smith and Richard D Lane and Thomas Parr and Karl J Friston [[bib]](bibtex.bib#L917-L927)
|
||||
- [**Simulating emotions: An active inference model of emotional state inference and emotion concept learning**](https://www.frontiersin.org/articles/10.3389/fpsyg.2019.02844/full) , (2019) by Ryan Smith and Thomas Parr and Karl J Friston [[bib]](bibtex.bib#L929-L939)
|
||||
- [**The hierarchical basis of neurovisceral integration**](https://www.sciencedirect.com/science/article/pii/S014976341630673X?casa_token=V0kmqFxZWg4AAAAA:QE5VJB7jp6k22u8L7S7iWYh2_EiLV9a4gyXGUfSMIXOte_zYxGsH2YXUkvKY6PeDKriYy8nu11o) , (2017) by Ryan Smith and Julian F Thayer and Sahib S Khalsa and Richard D Lane [[bib]](bibtex.bib#L947-L957)
|
||||
- [**Active inference in OpenAI gym: a paradigm for computational investigations into psychiatric illness**](https://www.sciencedirect.com/science/article/pii/S2451902218301617?casa_token=HRn2UHzCR18AAAAA:lTqZvwAL3WoYmchm2W2WYXKsastkTOVcEDpu9Fxtm5aZIfr6jmhexYHurChmmpFaNufNEpFuuPo) , (2018) by Maell Cullen and Ben Davey and Karl J Friston and Rosalyn J Moran [[bib]](bibtex.bib#L980-L991)
|
||||
- [**Active inference and robot control: a case study**](https://royalsocietypublishing.org/doi/full/10.1098/rsif.2016.0616) , (2016) by *Pio-Lopez, L{\'e}o, Nizard, Ange, Friston, Karl and Pezzulo, Giovanni* [[bib]](bibtex.bib#L734-L745)
|
||||
- [**Active inference body perception and action for humanoid robots**](https://arxiv.org/abs/1906.03022) , (2019) by *Oliver, Guillermo, Lanillos, Pablo and Cheng, Gordon* [[bib]](bibtex.bib#L746-L753)
|
||||
- [**End-to-end pixel-based deep active inference for body perception and action**](https://arxiv.org/abs/2001.05847) , (2019) by *Sancaktar, Cansu and Lanillos, Pablo* [[bib]](bibtex.bib#L754-L761)
|
||||
- [**Active inference for robot control: A factor graph approach**](https://pdfs.semanticscholar.org/e177/b21b0a7f43ad3969ceb42bd8f1d912ea8d43.pdf) , (2019) by *Vanderbroeck, Mees, Baioumy, Mohamed, van der Lans, Daan, de Rooij, Rens and van der Werf, Tiis* [[bib]](bibtex.bib#L762-L771)
|
||||
- [**A novel adaptive controller for robot manipulators based on active inference**](https://ieeexplore.ieee.org/abstract/document/9000729/?casa_token=OBL93SqhogUAAAAA:6w99NtC-Fk7P0tIiXx6QmTNsWnPS-GKK0OtsJEz-HWgniXwpY0Rtue_qlc5Fe9HQ2vj0ropx7hM) , (2020) by *Pezzato, Corrado, Ferrari, Riccardo and Corbato, Carlos Hern{\'a}ndez* [[bib]](bibtex.bib#L772-L783)
|
||||
|
||||
## Deep Active Inference
|
||||
- [**Reinforcement Learning through Active Inference**](https://arxiv.org/abs/2002.12636) , (2020) by Alexander Tschantz and Beren Millidge and Anil K Seth and Christopher L Buckley [[bib]](bibtex.bib#L649-L656)
|
||||
- [**Reinforcement Learning through Active Inference**](https://arxiv.org/abs/2002.12636) , (2020) by *Tschantz, Alexander, Millidge, Beren, Seth, Anil K and Buckley, Christopher L* [[bib]](bibtex.bib#L620-L627)
|
||||
|
||||
*Demonstrates that the exploration afforded by the Expected Free Energy Objective is useful in a deep reinforcement learning setting. Also maintains uncertainty through model ensembles applied in a model-based RL setting.*
|
||||
- [**Scaling active inference**](https://ieeexplore.ieee.org/abstract/document/9207382/?casa_token=TfYG9cq3UvwAAAAA:Fn2oE7PCTGHlEN0jPQQE4P-qBiO_V-7xRFXXqYn7ubVoZeoiBd6ViBAxWf1L7j-R1wiKEOKvaXQ) , (2020) by Alexander Tschantz and Manuel Baltieri and Anil K Seth and Christopher L Buckley [[bib]](bibtex.bib#L659-L668)
|
||||
- [**Scaling active inference**](https://ieeexplore.ieee.org/abstract/document/9207382/?casa_token=TfYG9cq3UvwAAAAA:Fn2oE7PCTGHlEN0jPQQE4P-qBiO_V-7xRFXXqYn7ubVoZeoiBd6ViBAxWf1L7j-R1wiKEOKvaXQ) , (2020) by *Tschantz, Alexander, Baltieri, Manuel, Seth, Anil K and Buckley, Christopher L* [[bib]](bibtex.bib#L630-L639)
|
||||
|
||||
*Implements Deep Active Inference in a model-based RL setting using explicit planning with a transition model.*
|
||||
- [**Deep active inference as variational policy gradients**](https://www.sciencedirect.com/science/article/pii/S0022249620300298?casa_token=GQLxvJzk3zMAAAAA:uotM5EqPWP9SIUV-5N8vvNnkVWSqFlS8W03MZ_W9GYCoyhWGRAhN9YmGjiTIaxCGHd4iwrjzElg) , (2020) by Beren Millidge [[bib]](bibtex.bib#L670-L680)
|
||||
- [**Deep active inference as variational policy gradients**](https://www.sciencedirect.com/science/article/pii/S0022249620300298?casa_token=GQLxvJzk3zMAAAAA:uotM5EqPWP9SIUV-5N8vvNnkVWSqFlS8W03MZ_W9GYCoyhWGRAhN9YmGjiTIaxCGHd4iwrjzElg) , (2020) by *Millidge, Beren* [[bib]](bibtex.bib#L641-L651)
|
||||
|
||||
*Implements deep active inference in a model-free policy gradient setting by amortising the learning of the expected-free-energy value function. Uses a transition model for the state-information gain term in the expected free energy.*
|
||||
- [**Deep active inference**](https://link.springer.com/article/10.1007/s00422-018-0785-7) , (2018) by Kai Ueltzh{\"o}ffer [[bib]](bibtex.bib#L682-L693)
|
||||
- [**Deep active inference**](https://link.springer.com/article/10.1007/s00422-018-0785-7) , (2018) by *Ueltzh{\"o}ffer, Kai* [[bib]](bibtex.bib#L653-L664)
|
||||
|
||||
*The first paper to try combining active inference with deep neural networks. Demonstrates the importance of the exploratory terms of the EFE to solve the mountain-car problem.*
|
||||
- [**Deep active inference agents using Monte-Carlo methods**](https://arxiv.org/abs/2006.04176) , (2020) by Zafeirios Fountas and Noor Sajid and Pedro AM Mediano and Karl Friston [[bib]](bibtex.bib#L696-L703)
|
||||
- [**Deep active inference agents using Monte-Carlo methods**](https://arxiv.org/abs/2006.04176) , (2020) by *Fountas, Zafeirios, Sajid, Noor, Mediano, Pedro AM and Friston, Karl* [[bib]](bibtex.bib#L667-L674)
|
||||
|
||||
|
||||
## Acknowledgements
|
||||
|
||||
Many thanks to @conorheins, Tomasz Korbak, Ryan Smith, Mel Andrews, Casper Hesp, and Manuel Baltieri for their helpful suggestions.
|
||||
Many thanks to @conorheins for his helpful suggestions.
|
||||
|
||||
|
||||
|
||||
|
|
|
|||
161
bibtex.bib
161
bibtex.bib
|
|
@ -22,22 +22,6 @@
|
|||
}
|
||||
@String(friston2010free="This provides a great overview for the initial intuitions behind the FEP and its application to the brain.")
|
||||
|
||||
@article{raja2021markov,
|
||||
title={The Markov Blanket Trick: On the Scope of the Free Energy Principle and Active Inference},
|
||||
author={Raja, Vicente and Valluri, Dinesh and Baggs, Edward and Chemero, Anthony and Aderson, Michael L},
|
||||
year={2021},
|
||||
keywords={philosophy},
|
||||
url={http://philsci-archive.pitt.edu/18831/1/The%20Markov%20Blanket%20Trick.pdf}
|
||||
}
|
||||
@article{aguilera2021particular,
|
||||
title={How particular is the physics of the Free Energy Principle?},
|
||||
author={Aguilera, Miguel and Millidge, Beren and Tschantz, Alexander and Buckley, Christopher L},
|
||||
journal={arXiv preprint arXiv:2105.11203},
|
||||
year={2021},
|
||||
keywords={philosophy},
|
||||
url={https://arxiv.org/pdf/2105.11203.pdf}
|
||||
}
|
||||
@String(aguilera2021particular="This paper critically analyses and deconstructs various philosophical claims about *what the FEP is saying*. Specifically, it argues that there is not necessarily a connection between the statistical notion of a Markov Blanket, and a functional notion, meaning that an actual *dynamical* separation (such as a cell membrane) does not necessarily imply a *statistical* separation in the form of a Markov Blanket and vice versa. Secondly, it demonstrates and clarifies that the FEP only makes claims about the flow of internal states *on average* over counterfactual realizations of the system, and therefore the FEP cannot describe the individual trajectories of a system in terms of free energy minimization.")
|
||||
|
||||
|
||||
@article{bogacz2017tutorial,
|
||||
|
|
@ -67,16 +51,6 @@
|
|||
}
|
||||
@String(buckley2017free="This is a fantastic review which presents a complete walkthrough of the mathematical basis of the Free Energy Principle and Variational Inference, and derives predictive coding and (continuous time and state) active inference. I would reccomend reading this after Bogacz' tutorial (although be prepared -- it is a long and serious read)")
|
||||
|
||||
@article{smith2021step,
|
||||
title={A Step-by-Step Tutorial on Active Inference and its Application to Empirical Data},
|
||||
author={Smith, Ryan and Friston, Karl and Whyte, Christopher},
|
||||
year={2021},
|
||||
publisher={PsyArXiv},
|
||||
keywords={survey},
|
||||
url={https://psyarxiv.com/b4jm6/}
|
||||
}
|
||||
@String(smith2021step="A detailed and clear walkthrough of discrete-state-space active inference, including detailed MATLAB code for a sample implementation.")
|
||||
|
||||
|
||||
@article{friston2019free,
|
||||
title={A free energy principle for a particular physics},
|
||||
|
|
@ -353,7 +327,6 @@
|
|||
keywords={classic},
|
||||
url={https://books.google.co.uk/books?hl=en&lr=&id=TnqECgAAQBAJ&oi=fnd&pg=PP1&dq=andy+clark+surfing+uncertainty&ots=aurm4jE3NO&sig=KxeHGJ6YJJdN9tKyr6snwDyBBKg&redir_esc=y#v=onepage&q=andy%20clark%20surfing%20uncertainty&f=false}
|
||||
}
|
||||
@String(friston2013life="A heuristic demonstration of the concept that Karl will later refer to as 'Bayesian mechanics', this paper surveys the notion that any random dynamical systems with the right kind of coupling among its sub-systems (i.e. a Markov blanket), will naturally appear as if it's performing a kind of approximate Bayesian inference. This argument is motivated by appeal to the existence of a non-equilibrium steady-state density, to which the system's probability distribution converges over time.")
|
||||
@article{friston2013life,
|
||||
title={Life as we know it},
|
||||
author={Friston, Karl},
|
||||
|
|
@ -412,7 +385,6 @@
|
|||
keywords={self-organisation},
|
||||
url={https://arxiv.org/abs/2006.02741}
|
||||
}
|
||||
@String(parr2020modules="The 'free energy' response to the Fodorian notion of 'modularity' as an explanation of functional segregation, here motivated by an appeal to the stochastic dynamics of Markov-blanketed systems. Parr et al. argue that, given a particular conditional independency structure among the components that comprise a random dynamical system, one can interpret the system and its dynamics as entertaining a mean-field factorised generative model of its local environment, as opposed to appealing to philosophically or otherwise-unsatisfying notions such as 'modularity'.")
|
||||
@article{parr2020modules,
|
||||
title={Modules or Mean-Fields?},
|
||||
author={Parr, Thomas and Sajid, Noor and Friston, Karl J},
|
||||
|
|
@ -435,7 +407,6 @@
|
|||
keywords={self-organisation},
|
||||
url={https://www.biorxiv.org/content/10.1101/227181v1.abstract}
|
||||
}
|
||||
@String(parr2020markov="This paper gives succinct and schematic treatments of several of the main concepts explored in a Free Energy Principle for a Particular Physics, particularly those related to Bayesian mechanics and information geometry. This work importantly delineates some of the conditions required of a system, so that its internal states approximately parameterise beliefs about external states. Fluctuation theorems are also invoked to relate the probability of trajectories or sequences of states to existing concepts in the active inference world, such as information gain, risk, and ambiguity resolution.")
|
||||
@article{parr2020markov,
|
||||
title={Markov blankets, information geometry and stochastic thermodynamics},
|
||||
author={Parr, Thomas and Da Costa, Lancelot and Friston, Karl},
|
||||
|
|
@ -594,7 +565,7 @@
|
|||
title={The Emperor’s New Markov Blankets},
|
||||
author={Bruineberg, Jelle and Dolega, Krzysztof and Dewhurst, Joe and Baltieri, Manuel},
|
||||
year={2020},
|
||||
keywords={self-organisation},
|
||||
keywords={self_organisation},
|
||||
url={http://philsci-archive.pitt.edu/18467/}
|
||||
}
|
||||
@article{friston2020sophisticated,
|
||||
|
|
@ -879,6 +850,40 @@
|
|||
url={https://www.tandfonline.com/doi/full/10.1080/17588928.2015.1026888?casa_token=IA7GL_oM2VAAAAAA%3AXkJ7HbhxHcW7qCdSWyRSerOo8iZevM3x_8QV1b7C7qAvAqJMveeq4IeGRBTCCbQOCJ6Ix9p70VkKww}
|
||||
}
|
||||
|
||||
@article{colombo2018,
|
||||
author = {Colombo, Matteo and Wright, Cory},
|
||||
year = {2018},
|
||||
month = {09},
|
||||
pages = {1–26},
|
||||
title = {First principles in the life sciences: The free-energy principle, organicism, and mechanism},
|
||||
journal = {Synthese},
|
||||
doi = {10.1007/s11229-018-01932-w},
|
||||
url = {https://link.springer.com/article/10.1007/s11229-018-01932-w},
|
||||
keywords={philosophy}
|
||||
}
|
||||
@article{allen2018cognitivism,
|
||||
title={From cognitivism to autopoiesis: towards a computational framework for the embodied mind},
|
||||
author={Allen, Micah and Friston, Karl J},
|
||||
journal={Synthese},
|
||||
volume={195},
|
||||
number={6},
|
||||
pages={2459--2482},
|
||||
year={2018},
|
||||
publisher={Springer},
|
||||
keywords={philosophy},
|
||||
url={https://link.springer.com/article/10.1007%2Fs11229-016-1288-5}
|
||||
}
|
||||
@article{korbak2019,
|
||||
author = {Korbak, Tomasz},
|
||||
year = {2019},
|
||||
month = {05},
|
||||
pages = {},
|
||||
title = {Computational enactivism under the free energy principle},
|
||||
journal = {Synthese},
|
||||
doi = {10.1007/s11229-019-02243-4},
|
||||
url = {https://link.springer.com/article/10.1007/s11229-019-02243-4},
|
||||
keywords={philosophy}
|
||||
}
|
||||
|
||||
@String(friston2008variational2="Foundational treatment of variational inference for dynamical systems, as represented in generalised coordinates. Also relates variational filtering to other non-variational schemes like particle filtering and Kalman filtering.")
|
||||
@article{friston2008variational2,
|
||||
|
|
@ -892,100 +897,4 @@
|
|||
publisher={Elsevier},
|
||||
keywords={classic},
|
||||
url={https://www.sciencedirect.com/science/article/pii/S1053811908002462?casa_token=bzK7h_aIzY0AAAAA:rg1CzE6vNo-cktIHO_9EAoqmR5Zpy89klEn-Wy3NAzMoR8NcWgaF5_zEzyhrRB76N5RPyCZTIlY}
|
||||
}
|
||||
|
||||
@article{smith2020recent,
|
||||
title={Recent advances in the application of predictive coding and active inference models within clinical neuroscience},
|
||||
author={Smith, Ryan and Badcock, Paul and Friston, Karl J},
|
||||
journal={Psychiatry and Clinical Neurosciences},
|
||||
year={2020},
|
||||
publisher={Wiley Online Library},
|
||||
keywords={applications},
|
||||
url={https://onlinelibrary.wiley.com/doi/abs/10.1111/pcn.13138}
|
||||
}
|
||||
@String(smith2020recent="A comprehensive review of neuroscientific and computational psychiatry applications of the FEP and Active Inference.")
|
||||
|
||||
@article{whyte2020predictive,
|
||||
title={The Predictive Global Neuronal Workspace: A Formal Active Inference Model of Visual Consciousness},
|
||||
author={Whyte, Christopher J and Smith, Ryan},
|
||||
journal={bioRxiv},
|
||||
year={2020},
|
||||
publisher={Cold Spring Harbor Laboratory},
|
||||
keywords={applications},
|
||||
url={https://www.sciencedirect.com/science/article/pii/S0301008220301738}
|
||||
}
|
||||
@article{smith2019neurocomputational,
|
||||
title={Neurocomputational mechanisms underlying emotional awareness: insights afforded by deep active inference and their potential clinical relevance},
|
||||
author={Smith, Ryan and Lane, Richard D and Parr, Thomas and Friston, Karl J},
|
||||
journal={Neuroscience \& Biobehavioral Reviews},
|
||||
volume={107},
|
||||
pages={473--491},
|
||||
year={2019},
|
||||
publisher={Elsevier},
|
||||
keywords={applications},
|
||||
url={https://www.sciencedirect.com/science/article/pii/S014976341930541X?casa_token=c1UILIbIsKYAAAAA:tQbclbvyieFsSPf_oqulTP8Manv6fU6CeI1iHGZe5Iq4TryLR4pGRjK0Y7RD4gZCfjJo02uWyvw}
|
||||
}
|
||||
|
||||
@article{smith2019simulating,
|
||||
title={Simulating emotions: An active inference model of emotional state inference and emotion concept learning},
|
||||
author={Smith, Ryan and Parr, Thomas and Friston, Karl J},
|
||||
journal={Frontiers in psychology},
|
||||
volume={10},
|
||||
pages={2844},
|
||||
year={2019},
|
||||
publisher={Frontiers},
|
||||
keywords={applications},
|
||||
url={https://www.frontiersin.org/articles/10.3389/fpsyg.2019.02844/full}
|
||||
}
|
||||
@article{andrews2020math,
|
||||
title={The Math is not the Territory: Navigating the Free Energy Principle},
|
||||
author={Andrews, Mel},
|
||||
year={2020},
|
||||
keywords={philosophy},
|
||||
url={http://philsci-archive.pitt.edu/18315/}
|
||||
}
|
||||
@article{smith2017hierarchical,
|
||||
title={The hierarchical basis of neurovisceral integration},
|
||||
author={Smith, Ryan and Thayer, Julian F and Khalsa, Sahib S and Lane, Richard D},
|
||||
journal={Neuroscience \& biobehavioral reviews},
|
||||
volume={75},
|
||||
pages={274--296},
|
||||
year={2017},
|
||||
publisher={Elsevier},
|
||||
keywords={applications},
|
||||
url={https://www.sciencedirect.com/science/article/pii/S014976341630673X?casa_token=V0kmqFxZWg4AAAAA:QE5VJB7jp6k22u8L7S7iWYh2_EiLV9a4gyXGUfSMIXOte_zYxGsH2YXUkvKY6PeDKriYy8nu11o}
|
||||
}
|
||||
@inproceedings{lanillos2018adaptive,
|
||||
title={Adaptive robot body learning and estimation through predictive coding},
|
||||
author={Lanillos, Pablo and Cheng, Gordon},
|
||||
booktitle={2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
|
||||
pages={4083--4090},
|
||||
year={2018},
|
||||
organization={IEEE},
|
||||
keywords={robotics},
|
||||
url={https://ieeexplore.ieee.org/document/8593684/}
|
||||
}
|
||||
@article{friston2010action,
|
||||
title={Action and behavior: a free-energy formulation},
|
||||
author={Friston, Karl J and Daunizeau, Jean and Kilner, James and Kiebel, Stefan J},
|
||||
journal={Biological cybernetics},
|
||||
volume={102},
|
||||
number={3},
|
||||
pages={227--260},
|
||||
year={2010},
|
||||
publisher={Springer},
|
||||
keywords={classic},
|
||||
url={https://link.springer.com/article/10.1007/s00422-010-0364-z}
|
||||
}
|
||||
@article{cullen2018active,
|
||||
title={Active inference in OpenAI gym: a paradigm for computational investigations into psychiatric illness},
|
||||
author={Cullen, Maell and Davey, Ben and Friston, Karl J and Moran, Rosalyn J},
|
||||
journal={Biological psychiatry: cognitive neuroscience and neuroimaging},
|
||||
volume={3},
|
||||
number={9},
|
||||
pages={809--818},
|
||||
year={2018},
|
||||
publisher={Elsevier},
|
||||
keywords={applications},
|
||||
url={https://www.sciencedirect.com/science/article/pii/S2451902218301617?casa_token=HRn2UHzCR18AAAAA:lTqZvwAL3WoYmchm2W2WYXKsastkTOVcEDpu9Fxtm5aZIfr6jmhexYHurChmmpFaNufNEpFuuPo}
|
||||
}
|
||||
|
|
@ -4,39 +4,18 @@ import collections
|
|||
|
||||
### utility function ###
|
||||
|
||||
FIRST_NAME_INITIAL = False
|
||||
|
||||
def swap_first_last_names(authors_str, initial_first=False):
|
||||
authors = authors_str.split(" and ")
|
||||
s = ""
|
||||
for author in authors:
|
||||
split_list = author.split(",")
|
||||
if len(split_list) == 2:
|
||||
last,first = split_list
|
||||
if initial_first:
|
||||
s += str(first[1]) + " " + str(last) + " and "
|
||||
else:
|
||||
s += str(first) + " " + str(last) + " and "
|
||||
else:
|
||||
print(split_list)
|
||||
s += str(split_list[0]) + " and "
|
||||
return s
|
||||
|
||||
|
||||
def keep_last_and_only(authors_str):
|
||||
"""
|
||||
This function is dedicated to parse authors, it removes all the "and" but the last and and replace them with ", "
|
||||
:param str: string with authors
|
||||
:return: string with authors with only one "and"
|
||||
"""
|
||||
authors_str = swap_first_last_names(authors_str,initial_first = FIRST_NAME_INITIAL)
|
||||
|
||||
last_author = authors_str.split(" and ")[-1]
|
||||
|
||||
without_and = authors_str.replace(" and ", ", ")
|
||||
|
||||
str_ok = without_and.replace(", " + last_author, " and " + last_author)
|
||||
# cut out final and
|
||||
str_ok = str_ok[:-4]
|
||||
|
||||
return str_ok
|
||||
|
||||
|
|
@ -93,7 +72,7 @@ def get_md_entry(DB, entry, add_comments=True):
|
|||
|
||||
md_str += ", (" + entry['year'] + ")"
|
||||
|
||||
md_str += " by " + keep_last_and_only(entry['author'])
|
||||
md_str += " by *" + keep_last_and_only(entry['author']) + "*"
|
||||
|
||||
md_str += " [[bib]](" + create_bib_link(entry['ID']) + ") "
|
||||
|
||||
|
|
@ -177,7 +156,7 @@ def get_AIF_outline(list_classif, filename):
|
|||
def get_acknowledgements():
|
||||
str_outline = "\n \n"
|
||||
str_outline += "## Acknowledgements \n \n"
|
||||
str_outline += "Many thanks to @conorheins, Tomasz Korbak, Ryan Smith, Mel Andrews, Casper Hesp, and Manuel Baltieri for their helpful suggestions. \n \n"
|
||||
str_outline += "Many thanks to @conorheins for his helpful suggestions. \n \n"
|
||||
return str_outline
|
||||
|
||||
def get_footnote_string():
|
||||
|
|
@ -251,7 +230,6 @@ if __name__ == '__main__':
|
|||
["Continuous Time Formulation","continuous"],
|
||||
["Message Passing and Free Energies","free_energy"],
|
||||
["Active Inference for Control Theory/Robotics","robotics"],
|
||||
["Neuroscience and Computational Psychiatry Applications","applications"],
|
||||
["Deep Active Inference", "deep"]]
|
||||
|
||||
generate_md_file(DB=bib_db, list_classif=FEP_list_types,AIF_list_classif=AIF_list_types, key="keywords", plot_title_fct=plot_titles, filename= "README.md", add_comments=True)
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue