On Markov blankets and hierarchical self-organisation

Highlight • Computational treatment of biological self-organisation.• Biological self-organisation requires emergence of boundaries, namely Markov blankets.• Hierarchical self-organisation entails emergence of Markov blankets at multiple scale.

[1]  Charles M. Bishop,et al.  Variational Message Passing , 2005, J. Mach. Learn. Res..

[2]  Marina Bosch,et al.  Applications Of Centre Manifold Theory , 2016 .

[3]  Harriet Finne-Soveri,et al.  Feasibility and baseline findings of an educational intervention in a randomized trial to optimize drug treatment among residents in assisted living facilities , 2014 .

[4]  Alan S. Perelson,et al.  Self-Organization in Nonequilibrium Systems. From Dissipative Structures to Order Through Fluctuations.G. Nicolis , I. Prigogine , 1978 .

[5]  Humberto R. Maturana,et al.  The organization of the living: A theory of the living organization , 1975 .

[6]  Karl J. Friston Life as we know it , 2013, Journal of The Royal Society Interface.

[7]  Karl J. Friston,et al.  Cognitive Dynamics: From Attractors to Active Inference , 2014, Proceedings of the IEEE.

[8]  Judea Pearl,et al.  Probabilistic reasoning in intelligent systems - networks of plausible inference , 1991, Morgan Kaufmann series in representation and reasoning.

[9]  Karl J. Friston,et al.  Action and behavior: a free-energy formulation , 2010, Biological Cybernetics.

[10]  M. N. Bera,et al.  Thermodynamics from Information , 2018, 1805.10282.

[11]  Hermann Haken,et al.  Synergetics: An Introduction , 1983 .

[12]  M P Young,et al.  Hierarchical organization of macaque and cat cortical sensory systems explored with a novel network processor. , 2000, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[13]  K. Cheng Theory of Superconductivity , 1948, Nature.

[14]  André Elisseeff,et al.  Using Markov Blankets for Causal Structure Learning , 2008, J. Mach. Learn. Res..

[15]  Michael Levin,et al.  Synchronization of Bioelectric Oscillations in Networks of Nonexcitable Cells: From Single-Cell to Multicellular States. , 2019, The journal of physical chemistry. B.

[16]  H. Haken,et al.  Intentionality in non-equilibrium systems? The functional aspects of self-organized pattern formation , 2007 .

[17]  H. Maturana,et al.  Autopoiesis: the organization of living systems, its characterization and a model. , 1974, Currents in modern biology.

[18]  Jeremy L. England,et al.  Statistical physics of self-replication. , 2012, The Journal of chemical physics.

[19]  Takayuki Ito,et al.  Holonic Multiagent Simulation of Complex Adaptive Systems , 2016, PAAMS.

[20]  A. Clark How to Knit Your Own Markov Blanket: Resisting the Second Law with Metamorphic Minds , 2017 .

[21]  Gennaro Auletta,et al.  A Paradigm Shift in Biology? , 2010, Inf..

[22]  Yuhong Yang,et al.  Information Theory, Inference, and Learning Algorithms , 2005 .

[23]  Randall D. Beer,et al.  The Cognitive Domain of a Glider in the Game of Life , 2014, Artificial Life.

[24]  J. Hohwy The self-evidencing brain , 2016 .

[25]  George F. R. Ellis,et al.  Top-down causation: an integrating theme within and across the sciences? , 2012, Interface Focus.

[26]  S. Frank Natural selection. V. How to read the fundamental equations of evolutionary change in terms of information theory , 2012, Journal of evolutionary biology.

[27]  Karl J. Friston,et al.  Answering Schrödinger's question: A free-energy formulation , 2017, Physics of life reviews.

[28]  David J. C. MacKay,et al.  Information Theory, Inference, and Learning Algorithms , 2004, IEEE Transactions on Information Theory.

[29]  Karl J. Friston,et al.  Morphogenesis as Bayesian inference: A variational approach to pattern formation and control in complex biological systems. , 2020, Physics of life reviews.

[30]  W. Ashby,et al.  Every Good Regulator of a System Must Be a Model of That System , 1970 .

[31]  Karl J. Friston,et al.  A Hierarchy of Time-Scales and the Brain , 2008, PLoS Comput. Biol..

[32]  H. Crauel,et al.  Attractors for random dynamical systems , 1994 .

[33]  R. Landauer,et al.  Irreversibility and heat generation in the computing process , 1961, IBM J. Res. Dev..

[34]  Ludovico Cademartiri,et al.  Using shape for self-assembly , 2012, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[35]  F. Schwabl,et al.  Phase Transitions, Scale Invariance, Renormalization Group Theory, and Percolation , 2002 .

[36]  Stuart A. Kauffman,et al.  ORIGINS OF ORDER , 2019, Origins of Order.

[37]  Karl J. Friston,et al.  Life and Understanding: The Origins of “Understanding” in Self-Organizing Nervous Systems , 2016, Front. Syst. Neurosci..

[38]  Humberto R. Maturana,et al.  The Organization of the Living , 1999 .

[39]  Tetsuya Tabata,et al.  Morphogens, their identification and regulation , 2004, Development.

[40]  Debra J. Searles,et al.  The Fluctuation Theorem , 2002 .

[41]  J. Fincham,et al.  At Home in the Universe: the Search for Laws of Complexity . By Stuart Kauffman. Viking 1995. viii + 321 pages. Hard cover. Price £20. ISBN 0 670 84735 6. , 1996 .

[42]  Karl J. Friston,et al.  Active Inference: A Process Theory , 2017, Neural Computation.

[43]  Karl J. Friston,et al.  Generalised Filtering , 2010 .

[44]  Hans Crauel,et al.  Global random attractors are uniquely determined by attracting deterministic compact sets , 1999 .

[45]  Humberto Maturana Romesín The Organization of the Living: A Theory of the Living Organization , 1975, Int. J. Hum. Comput. Stud..

[46]  S. Kauffman At Home in the Universe: The Search for the Laws of Self-Organization and Complexity , 1995 .

[47]  Diana M. Mitrea,et al.  Phase separation in biology; functional organization of a higher order , 2016, Cell Communication and Signaling.

[48]  Nathaniel Virgo,et al.  The Role of the Spatial Boundary in Autopoiesis , 2009, ECAL.

[49]  P. Ao Global view of bionetwork dynamics: adaptive landscape. , 2009, Journal of genetics and genomics = Yi chuan xue bao.

[50]  Judea Pearl,et al.  Probabilistic reasoning in intelligent systems , 1988 .

[51]  G. Whitesides,et al.  Self-Assembly at All Scales , 2002, Science.

[52]  Brian Charlesworth Kauffman's ‘origins of order’. Making evolution seem complicated , 1995 .

[53]  Andy Clark,et al.  How to Knit Your Own Markov Blanket , 2017 .

[54]  James Briscoe,et al.  Gene Regulatory Logic for Reading the Sonic Hedgehog Signaling Gradient in the Vertebrate Neural Tube , 2012, Cell.

[55]  Mirko Farina Supersizing the Mind: Embodiment, Action and Cognitive Extension. , 2010 .

[56]  Ralf Der,et al.  Predictive information and explorative behavior of autonomous robots , 2008 .

[57]  Carlos Gershenson,et al.  Guiding the self-organization of random Boolean networks , 2010, Theory in Biosciences.

[58]  Christopher L. Buckley,et al.  A Probabilistic Interpretation of PID Controllers Using Active Inference , 2018, SAB.

[59]  Juan Camilo Ramírez,et al.  Can natural selection encode Bayesian priors? , 2017, Journal of theoretical biology.

[60]  Micah Allen The foundation: Mechanism, prediction, and falsification in Bayesian enactivism: Comment on "Answering Schrödinger's question: A free-energy formulation" by Maxwell James Désormeau Ramstead et al. , 2018, Physics of life reviews.

[61]  C. Jarzynski Nonequilibrium Equality for Free Energy Differences , 1996, cond-mat/9610209.

[62]  U. Seifert Stochastic thermodynamics, fluctuation theorems and molecular machines , 2012, Reports on progress in physics. Physical Society.

[63]  Erwin Frey,et al.  Self-organization principles of intracellular pattern formation , 2018, Philosophical Transactions of the Royal Society B: Biological Sciences.

[64]  Wilson S. Geisler,et al.  A Bayesian approach to the evolution of perceptual and cognitive systems , 2003, Cogn. Sci..

[65]  E. Schrödinger What is life? : the physical aspect of the living cell , 1944 .

[66]  David Botstein,et al.  Diversity, topographic differentiation, and positional memory in human fibroblasts , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[67]  N. Fytas,et al.  Dynamic phase transition of the Blume-Capel model in an oscillating magnetic field. , 2017, Physical review. E.

[68]  Charles H. Bennett,et al.  Notes on Landauer's Principle, Reversible Computation, and Maxwell's Demon , 2002, physics/0210005.

[69]  J. Fuster Upper processing stages of the perception–action cycle , 2004, Trends in Cognitive Sciences.

[70]  M. Tribus Information Theory as the Basis for Thermostatics and Thermodynamics , 1961 .

[71]  Karl J. Friston,et al.  Free Energy, Value, and Attractors , 2011, Comput. Math. Methods Medicine.

[72]  Viktor K. Jirsa,et al.  Time Scale Hierarchies in the Functional Organization of Complex Behaviors , 2011, PLoS Comput. Biol..

[73]  Jun Tani,et al.  Self-Organization of Spatio-Temporal Hierarchy via Learning of Dynamic Visual Image Patterns on Action Sequences , 2015, PloS one.

[74]  Ken Sekimoto,et al.  Langevin Equation and Thermodynamics , 1998 .

[75]  Karl J. Friston The free-energy principle: a unified brain theory? , 2010, Nature Reviews Neuroscience.

[76]  Gennaro Auletta,et al.  Information and Metabolism in Bacterial Chemotaxis , 2013, Entropy.

[77]  N. Virgo Thermodynamics and the structure of living systems , 2011 .

[78]  Kate Jeffery,et al.  On the Statistical Mechanics of Life: Schrödinger Revisited , 2019, Entropy.

[79]  John O. Campbell Universal Darwinism As a Process of Bayesian Inference , 2016, Front. Syst. Neurosci..

[80]  V. Araújo Random Dynamical Systems , 2006, math/0608162.

[81]  Karl J. Friston A free energy principle for a particular physics , 2019, 1906.10184.

[82]  S. Alberti Phase separation in biology , 2017, Current Biology.

[83]  Karl J. Friston,et al.  The Markov blankets of life: autonomy, active inference and the free energy principle , 2018, Journal of The Royal Society Interface.

[84]  T. D. Frank,et al.  Stochastic feedback, nonlinear families of Markov processes, and nonlinear Fokker–Planck equations , 2004 .

[85]  Jeffrey K. Noel,et al.  The Dominant Folding Route Minimizes Backbone Distortion in SH3 , 2012, PLoS Comput. Biol..

[86]  Karl J. Friston,et al.  Knowing one's place: a free-energy approach to pattern regulation , 2015, Journal of The Royal Society Interface.