Information theory , predictability, and the emergence of complex life
Luís F Seoane 1, 2, 3 and Ricard V. Solé 2, 3, 4
1 Department of Physics, Massachusetts Institute of Technology, Cambridge, MA 02139.
2 ICREA-Complex Systems Lab, Universitat Pompeu Fabra (GRIB), Dr Aiguader 80, 08003 Barcelona, Spain.
3 Institut de Biologia Evolutiva, CSIC-UPF, Pg Maritim de la Barceloneta 37, 08003 Barcelona, Spain.
4 Santa Fe Institute, 1399 Hyde Park Road, Santa Fe NM 87501, USA.
Source/Fonte: Jon Lieff
Abstract
Despite the obvious advantage of simple life forms capable of fast replication, different levels of cognitive complexity have been achieved by living systems in terms of their potential to cope with environmental uncertainty. Against the inevitable cost associated to detecting environmental cues and responding to them in adaptive ways, we conjecture that the potential for predicting the environment can overcome the expenses associated to maintaining costly, complex structures. We present a minimal formal model grounded in information theory and selection, in which successive generations of agents are mapped into transmitters and receivers of a coded message. Our agents are guessing machines and their capacity to deal with environments of different complexity defines the conditions to sustain more complex agents.
Keywords: Complexity, emergence, computation, evolution, predictability
