Exploring the Space of Viable Configurations in a Model of Metabolism–Boundary Co-construction

We introduce a spatial model of concentration dynamics that supports the emergence of spatiotemporal inhomogeneities that engage in metabolism–boundary co-construction. These configurations exhibit disintegration following some perturbations, and self-repair in response to others. We define robustness as a viable configuration's tendency to return to its prior configuration in response to perturbations, and plasticity as a viable configuration's tendency to change to other viable configurations. These properties are demonstrated and quantified in the model, allowing us to map a space of viable configurations and their possible transitions. Combining robustness and plasticity provides a measure of viability as the average expected survival time under ongoing perturbation, and allows us to measure how viability is affected as the configuration undergoes transitions. The framework introduced here is independent of the specific model we used, and is applicable for quantifying robustness, plasticity, and viability in any computational model of artificial life that demonstrates the conditions for viability that we promote.

[1]  G. Marsaglia Choosing a Point from the Surface of a Sphere , 1972 .

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

[3]  Milan Zeleny,et al.  SELF-ORGANIZATION OF LIVING SYSTEMS: A FORMAL MODEL OF AUTOPOIESIS , 1977 .

[4]  M. Eigen,et al.  The Hypercycle: A principle of natural self-organization , 2009 .

[5]  S. Kauffman Autocatalytic sets of proteins. , 1986 .

[6]  M. Conrad The geometry of evolution. , 1990, Bio Systems.

[7]  W. Fontana,et al.  “The arrival of the fittest”: Toward a theory of biological organization , 1994 .

[8]  Lawrence F. Shampine,et al.  The MATLAB ODE Suite , 1997, SIAM J. Sci. Comput..

[9]  John S. McCaskill,et al.  Evolving Reaction-Diffusion Ecosystems with Self-Assembling Structures in Thin Films , 1998, Artificial Life.

[10]  Takashi Ikegami,et al.  Model of Self-Replicating Cell Capable of Self-Maintenance , 1999, ECAL.

[11]  U. Alon,et al.  Robustness in bacterial chemotaxis , 2022 .

[12]  T. Ikegami,et al.  Self-maintenance and self-reproduction in an abstract cell model. , 2000, Journal of theoretical biology.

[13]  G. Wagner,et al.  The topology of the possible: formal spaces underlying patterns of evolutionary change. , 2001, Journal of theoretical biology.

[14]  Takashi Ikegami,et al.  Artificial Chemistry: Computational Studies on the Emergence of Self-Reproducing Units , 2001, ECAL.

[15]  F. Varela,et al.  Life after Kant: Natural purposes and the autopoietic foundations of biological individuality , 2002 .

[16]  John N. Tsitsiklis,et al.  Introduction to Probability , 2002 .

[17]  Humberto Maturana Romesín Autopoiesis, Structural Coupling and Cognition: A history of these and other notions in the biology of cognition , 2002, Cybern. Hum. Knowing.

[18]  M. West-Eberhard Developmental plasticity and evolution , 2003 .

[19]  Randall D. Beer,et al.  Autopoiesis and Cognition in the Game of Life , 2004, Artificial Life.

[20]  Hiroaki Kitano,et al.  Biological robustness , 2008, Nature Reviews Genetics.

[21]  Paul Bourgine,et al.  Autopoiesis and Cognition , 2004, Artificial Life.

[22]  Barry McMullin,et al.  Thirty Years of Computational Autopoiesis: A Review , 2004, Artificial Life.

[23]  E. D. Paolo,et al.  Autopoiesis, Adaptivity, Teleology, Agency , 2005 .

[24]  Pietro Speroni di Fenizio,et al.  Chemical Organisation Theory , 2005, Bulletin of mathematical biology.

[25]  C. Wilke,et al.  Robustness and Evolvability in Living Systems , 2006 .

[26]  Tim J. Hutton,et al.  Evolvable Self-Reproducing Cells in a Two-Dimensional Artificial Chemistry , 2007, Artificial Life.

[27]  Peter Dittrich,et al.  Chemical Organisation Theory , 2007, Bulletin of mathematical biology.

[28]  Ezequiel A. Di Paolo,et al.  Integrating Autopoiesis and Behavior: An Exploration in Computational Chemo-ethology , 2009, Adapt. Behav..

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

[30]  Takashi Ikegami,et al.  Shapes and Self-Movement in Protocell Systems , 2009, Artificial Life.

[31]  M. Rohde,et al.  Horizons for the Enactive Mind: Values, Social Interaction, and Play , 2010 .

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

[33]  P. Gluckman,et al.  Plasticity, robustness, development and evolution. , 2011, International journal of epidemiology.

[34]  Nathaniel Virgo,et al.  Motility at the Origin of Life: Its Characterization and a Model , 2013, Artificial Life.

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

[36]  Eran Agmon,et al.  Quantifying Robustness in a Spatial Model of Metabolism-Boundary Co-Construction , 2014, ALIFE.

[37]  Paul Bourgine,et al.  A Hybrid Off/On-Lattice Model of Emergence and Maintenance Autopoiesis , 2014 .

[38]  Xabier E. Barandiaran,et al.  Norm-Establishing and Norm-Following in Autonomous Agency , 2014, Artificial Life.