LEADER 04509nam 2201093z- 450 001 9910674391803321 005 20231214132942.0 035 $a(CKB)5600000000483015 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/91238 035 $a(EXLCZ)995600000000483015 100 $a20202208d2022 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aApplying the Free-Energy Principle to Complex Adaptive Systems 210 $aBasel$cMDPI - Multidisciplinary Digital Publishing Institute$d2022 215 $a1 electronic resource (214 p.) 311 $a3-0365-4773-8 311 $a3-0365-4774-6 330 $aThe free energy principle is a mathematical theory of the behaviour of self-organising systems that originally gained prominence as a unified model of the brain. Since then, the theory has been applied to a plethora of biological phenomena, extending from single-celled and multicellular organisms through to niche construction and human culture, and even the emergence of life itself. The free energy principle tells us that perception and action operate synergistically to minimize an organism?s exposure to surprising biological states, which are more likely to lead to decay. A key corollary of this hypothesis is active inference?the idea that all behavior involves the selective sampling of sensory data so that we experience what we expect to (in order to avoid surprises). Simply put, we act upon the world to fulfill our expectations. It is now widely recognized that the implications of the free energy principle for our understanding of the human mind and behavior are far-reaching and profound. To date, however, its capacity to extend beyond our brain?to more generally explain living and other complex adaptive systems?has only just begun to be explored. The aim of this collection is to showcase the breadth of the free energy principle as a unified theory of complex adaptive systems?conscious, social, living, or not. 606 $aInformation technology industries$2bicssc 606 $aComputer science$2bicssc 610 $amessage passing 610 $ametabolism 610 $aBayesian 610 $astochastic 610 $anon-equilibrium 610 $amaster equations 610 $acancer niches 610 $afree energy 610 $aKikuchi approximations 610 $aapoptosis 610 $ametastasis 610 $acluster variation method 610 $aFree Energy Principle 610 $aactive inference 610 $aBayesian brain 610 $agenerative models 610 $acybernetics 610 $aembodiment 610 $aenactivism 610 $acognitivism 610 $arepresentations 610 $aconsciousness 610 $afree will 610 $amental causation 610 $acognitive-affective development 610 $aemotions 610 $afeelings 610 $areadiness potentials 610 $aintentionality 610 $aagency 610 $aintelligence 610 $acollective intelligence 610 $afree energy principle 610 $aagent-based model 610 $acomplex adaptive systems 610 $amultiscale systems 610 $acomputational model 610 $auncertainty 610 $aPOMDP 610 $aemotion 610 $aaffect control theory 610 $asociology 610 $apermutation entropy 610 $adisorder 610 $astress 610 $aallostatic (hub) overload 610 $acascading failure 610 $adisease 610 $ahierarchical control systems 610 $acritical slowing down 610 $amodel-based control 610 $aadaptive robots 610 $agenerative model 610 $aBayesian inference 610 $afiltering 610 $aneurotechnology 615 7$aInformation technology industries 615 7$aComputer science 700 $aBadcock$b Paul$4edt$01338459 702 $aRamstead$b Maxwell$4edt 702 $aSheikhbahaee$b Zahra$4edt 702 $aConstant$b Axel$4edt 702 $aBadcock$b Paul$4oth 702 $aRamstead$b Maxwell$4oth 702 $aSheikhbahaee$b Zahra$4oth 702 $aConstant$b Axel$4oth 906 $aBOOK 912 $a9910674391803321 996 $aApplying the Free-Energy Principle to Complex Adaptive Systems$93058546 997 $aUNINA