Emergence as Mesoscopic Coherence

We propose here a formal approach to study collective behaviors intended as coherent sequences of spatial configurations, adopted by agents through various corresponding structures over time. Multiple, simultaneous structures over time and their sequences are called Meta-Structures and establish sequences of spatial configurations considered as emergent on the basis of coherent criteria chosen and detected by an observer. This coherence is represented by patterns of values of the proper mesoscopic variables adopted, i.e., meta-structural properties. We introduce a formal tool, i.e., the family of mesoscopic general vectors, defined by the observer, able to detect coherent behaviors like ergodic or quasi-ergodic ones. Such approach aims to provide a general framework to study intrinsically stochastic processes where the “universal evolution laws” fail. However, at the same, the system is structured enough to show significant clusters of collective behaviors “invisible to” simple statistics.

[1]  Gianfranco Minati,et al.  Methods, Models, Simulations And Approaches Towards A General Theory Of Change , 2011 .

[2]  Eliano Pessa,et al.  Physical and Biological Emergence: Are They Different? , 2006 .

[3]  H. Haken.  Advanced Synergetics: Instability Hierarchies of Self-Organizing Systems and Devices , 1983 .

[4]  G. Minati,et al.  COLLECTIVE BEINGS , 2013 .

[5]  D. Knoke.  Understanding Social Networks: Theories, Concepts, and Findings , 2013 .

[6]  Masoud Nikravesh,et al.  Morphic computing , 2008, Appl. Soft Comput..

[7]  Ignazio Licata.  Logical openness in cognitive models , 2008 .

[8]  J. Crutchfield.  The calculi of emergence: computation, dynamics and induction , 1994 .

[9]  I. Licata.  Emergence and Computation at the Edge of Classical and Quantum Systems , 2007, 0711.2973.

[10]  I. Licata.  Seeing by Models: Vision as Adaptative Epistemology , 2012 .

[11]  G. Parisi,et al.  Interaction ruling animal collective behavior depends on topological rather than metric distance: Evidence from a field study , 2007, Proceedings of the National Academy of Sciences.

[12]  Manfred Schroeder,et al.  Fractals, Chaos, Power Laws: Minutes From an Infinite Paradise , 1992 .

[13]  P. Wolynes,et al.  The middle way. , 2000, Proceedings of the National Academy of Sciences of the United States of America.

[14]  Stephen Wolfram,et al.  A New Kind of Science , 2003, Artificial Life.

[15]  Giorgio Panin,et al.  Model-based Visual Tracking: The OpenTL Framework , 2011 .

[16]  Moshe Sipper,et al.  Design, Observation, Surprise! A Test of Emergence , 1999, Artificial Life.

[17]  Mark Newman,et al.  Networks: An Introduction , 2010 .

[18]  R. R. Krausz.  Living in Groups , 2013 .

[19]  E. Pessa.  Phase Transitions in Biological Matter , 2008 .

[20]  Gianfranco Minati,et al.  Creativity as Cognitive design The case of mesoscopic variables in Meta-Structures , 2009 .

[21]  I. Licata.  Vision as Adaptive Epistemology , 2008, 0812.0115.

[22]  Gianfranco Minati,et al.  Emergence and Ergodicity: A Line of Research , 2002 .

[23]  Eliano Pessa.  ON MODELS OF EMERGENT METASTRUCTURES , 2012 .

[24]  Gianfranco Minati,et al.  Meta-structural properties in collective behaviours , 2012, Int. J. Gen. Syst..

[25]  Andrea Cavagna,et al.  Superfluid transport of information in turning flocks of starlings , 2013, 1303.7097.

[26]  Alessandro Palombo,et al.  Theoretical aspects of Systems Biology. , 2013, Progress in biophysics and molecular biology.

[27]  Ignazio Licata.  Almost-anywhere theories: Reductionism and universality of emergence , 2010 .

[28]  Germano Resconi,et al.  INFORMATION AS ENVIRONMENT CHANGINGS CLASSICAL AND QUANTUM MORPHIC COMPUTATION , 2011 .

[29]  Duncan J. Watts,et al.  The Structure and Dynamics of Networks: (Princeton Studies in Complexity) , 2006 .

[30]  Gianfranco Minati,et al.  Meta-Structures: The Search of Coherence in Collective Behaviours (without Physics) , 2013, Wivace.

[31]  I. Licata.  Living With Radical Uncertainty. The Exemplary case of Folding Protein , 2010, 1004.4587.

[32]  H. Stanley,et al.  The Physics of Foraging: An Introduction to Random Searches and Biological Encounters , 2011 .

[33]  Alex J. Ryan,et al.  Emergence is coupled to scope, not level , 2006, Complex..

[34]  T. Vicsek,et al.  Collective Motion , 1999, physics/9902023.

[35]  S. Havlin,et al.  Fractals and Disordered Systems , 1991 .

[36]  Andrea Cavagna,et al.  Information transfer and behavioural inertia in starling flocks , 2013, Nature Physics.