000070892 001__ 70892
000070892 005__ 20191122145054.0
000070892 0247_ $$2doi$$a10.1038/s41598-018-25925-4
000070892 0248_ $$2sideral$$a106368
000070892 037__ $$aART-2018-106368
000070892 041__ $$aeng
000070892 100__ $$0(orcid)0000-0002-3366-4706$$aAguilera, M.
000070892 245__ $$aAdaptation to criticality through organizational invariance in embodied agents
000070892 260__ $$c2018
000070892 5060_ $$aAccess copy available to the general public$$fUnrestricted
000070892 5203_ $$aMany biological and cognitive systems do not operate deep within one or other regime of activity. Instead, they are poised at critical points located at phase transitions in their parameter space. The pervasiveness of criticality suggests that there may be general principles inducing this behaviour, yet there is no well-founded theory for understanding how criticality is generated at a wide span of levels and contexts. In order to explore how criticality might emerge from general adaptive mechanisms, we propose a simple learning rule that maintains an internal organizational structure from a specific family of systems at criticality. We implement the mechanism in artificial embodied agents controlled by a neural network maintaining a correlation structure randomly sampled from an Ising model at critical temperature. Agents are evaluated in two classical reinforcement learning scenarios: the Mountain Car and the Acrobot double pendulum. In both cases the neural controller appears to reach a point of criticality, which coincides with a transition point between two regimes of the agent''s behaviour. These results suggest that adaptation to criticality could be used as a general adaptive mechanism in some circumstances, providing an alternative explanation for the pervasive presence of criticality in biological and cognitive systems.
000070892 536__ $$9info:eu-repo/grantAgreement/ES/MINECO/PSI2014-62092-EXP$$9info:eu-repo/grantAgreement/ES/MINECO/TIN2016-80347-R
000070892 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/
000070892 590__ $$a4.011$$b2018
000070892 591__ $$aMULTIDISCIPLINARY SCIENCES$$b14 / 69 = 0.203$$c2018$$dQ1$$eT1
000070892 592__ $$a1.414$$b2018
000070892 593__ $$aMultidisciplinary$$c2018$$dQ1
000070892 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000070892 700__ $$0(orcid)0000-0002-8263-2444$$aGonzález Bedia, M.$$uUniversidad de Zaragoza
000070892 7102_ $$15007$$2570$$aUniversidad de Zaragoza$$bDpto. Informát.Ingenie.Sistms.$$cÁrea Lenguajes y Sistemas Inf.
000070892 773__ $$g8, 1 (2018), 7723 [11 pp]$$pSci. rep.$$tSCIENTIFIC REPORTS$$x2045-2322
000070892 8564_ $$s6191434$$uhttps://zaguan.unizar.es/record/70892/files/texto_completo.pdf$$yVersión publicada
000070892 8564_ $$s112662$$uhttps://zaguan.unizar.es/record/70892/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000070892 909CO $$ooai:zaguan.unizar.es:70892$$particulos$$pdriver
000070892 951__ $$a2019-11-22-14:44:50
000070892 980__ $$aARTICLE