title: Information-based fitness and the emergence of criticality in living systems.
abstract: Empirical evidence suggesting that living systems might operate in the vicinity of critical points, at the borderline between order and disorder, has proliferated in recent years, with examples ranging from spontaneous brain activity to flock dynamics. However, a well-founded theory for understanding how and why interacting living systems could dynamically tune themselves to be poised in the vicinity of a critical point is lacking. Here we use tools from statistical mechanics and information theory to show that complex adaptive or evolutionary systems can be much more efficient in coping with diverse heterogeneous environmental conditions when operating at criticality. Analytical as well as computational evolutionary and adaptive models vividly illustrate that a community of such systems dynamically self-tunes close to a critical state as the complexity of the environment increases while they remain noncritical for simple and predictable environments. A more robust convergence to criticality emerges in coevolutionary and coadaptive setups in which individuals aim to represent other agents in the community with fidelity, thereby creating a collective critical ensemble and providing the best possible tradeoff between accuracy and flexibility. Our approach provides a parsimonious and general mechanism for the emergence of critical-like behavior in living systems needing to cope with complex environments or trying to efficiently coordinate themselves as an ensemble.
authors: Departamento de Electromagnetismo y Física de la Materia and Instituto Carlos I de Física Teórica y Computacional, Universidad de Granada, 18071 Granada, Spain;
authors: Jorge
authors: J
authors: Hidalgo
authors: Dipartimento di Fisica "G. Galilei", Consorzio Nazionale Interuniversitario per le Scienze Fisiche della Materia and Istituto Nazionale di Fisica Nucleare, Università di Padova, 35131 Padua, Italy; and.
authors: Jacopo
authors: J
authors: Grilli
authors: Dipartimento di Fisica "G. Galilei", Consorzio Nazionale Interuniversitario per le Scienze Fisiche della Materia and Istituto Nazionale di Fisica Nucleare, Università di Padova, 35131 Padua, Italy; and.
authors: Samir
authors: S
authors: Suweis
authors: Departamento de Electromagnetismo y Física de la Materia and Instituto Carlos I de Física Teórica y Computacional, Universidad de Granada, 18071 Granada, Spain; mamunoz@onsager.ugr.es amos.maritan@pd.infn.it.
authors: Miguel A
authors: MA
authors: Muñoz
authors: Department of Physics, University of Maryland, College Park, MD 20742.
authors: Jayanth R
authors: JR
authors: Banavar
authors: Dipartimento di Fisica "G. Galilei", Consorzio Nazionale Interuniversitario per le Scienze Fisiche della Materia and Istituto Nazionale di Fisica Nucleare, Università di Padova, 35131 Padua, Italy; and mamunoz@onsager.ugr.es amos.maritan@pd.infn.it.
authors: Amos
authors: A
authors: Maritan
mesh_terms: D000818:Animals; D001921:Brain / Q000502:physiology*; D006801:Humans; D008959:Models, Neurological
keywords: adaptation; evolution; self-organization