70892 20191122145054.0 doi 10.1038/s41598-018-25925-4 sideral 106368 ART-2018-106368 eng (orcid)0000-0002-3366-4706 Aguilera, M. Adaptation to criticality through organizational invariance in embodied agents 2018 Access copy available to the general public Unrestricted Many biological and cognitive systems do not operate deep within one or other regime of activity. Instead, they are poised at critical points located at phase transitions in their parameter space. The pervasiveness of criticality suggests that there may be general principles inducing this behaviour, yet there is no well-founded theory for understanding how criticality is generated at a wide span of levels and contexts. In order to explore how criticality might emerge from general adaptive mechanisms, we propose a simple learning rule that maintains an internal organizational structure from a specific family of systems at criticality. We implement the mechanism in artificial embodied agents controlled by a neural network maintaining a correlation structure randomly sampled from an Ising model at critical temperature. Agents are evaluated in two classical reinforcement learning scenarios: the Mountain Car and the Acrobot double pendulum. In both cases the neural controller appears to reach a point of criticality, which coincides with a transition point between two regimes of the agent''s behaviour. These results suggest that adaptation to criticality could be used as a general adaptive mechanism in some circumstances, providing an alternative explanation for the pervasive presence of criticality in biological and cognitive systems. info:eu-repo/grantAgreement/ES/MINECO/PSI2014-62092-EXP info:eu-repo/grantAgreement/ES/MINECO/TIN2016-80347-R info:eu-repo/semantics/openAccess by http://creativecommons.org/licenses/by/3.0/es/ 4.011 2018 MULTIDISCIPLINARY SCIENCES 14 / 69 = 0.203 2018 Q1 T1 1.414 2018 Multidisciplinary 2018 Q1 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion (orcid)0000-0002-8263-2444 González Bedia, M. Universidad de Zaragoza 5007 570 Universidad de Zaragoza Dpto. Informát.Ingenie.Sistms. Área Lenguajes y Sistemas Inf. 8, 1 (2018), 7723 [11 pp] Sci. rep. SCIENTIFIC REPORTS 2045-2322 6191434 http://zaguan.unizar.es/record/70892/files/texto_completo.pdf Versión publicada 112662 http://zaguan.unizar.es/record/70892/files/texto_completo.jpg?subformat=icon icon Versión publicada oai:zaguan.unizar.es:70892 articulos driver 2019-11-22-14:44:50 ARTICLE