001446791 000__ 04697cam\a2200565Ii\4500
001446791 001__ 1446791
001446791 003__ OCoLC
001446791 005__ 20230310004017.0
001446791 006__ m\\\\\o\\d\\\\\\\\
001446791 007__ cr\un\nnnunnun
001446791 008__ 220520s2022\\\\gw\a\\\\ob\\\\001\0\eng\d
001446791 019__ $$a1319199858$$a1319222609
001446791 020__ $$a9783662649855$$q(electronic bk.)
001446791 020__ $$a3662649853$$q(electronic bk.)
001446791 020__ $$z9783662649831
001446791 020__ $$z3662649837
001446791 0247_ $$a10.1007/978-3-662-64985-5$$2doi
001446791 035__ $$aSP(OCoLC)1319074733
001446791 040__ $$aYDX$$beng$$erda$$epn$$cYDX$$dGW5XE$$dEBLCP$$dOCLCF$$dUKAHL$$dOCLCQ
001446791 049__ $$aISEA
001446791 050_4 $$aQA76.9.A43
001446791 08204 $$a005.1$$223/eng/20220527
001446791 1001_ $$aZenil, Hector,$$eauthor.
001446791 24510 $$aMethods and applications of algorithmic complexity :$$bbeyond statistical lossless compression /$$cHector Zenil, Fernando Soler Toscano, Nicolas Gauvrit.
001446791 264_1 $$aBerlin :$$bSpringer,$$c[2022]
001446791 264_4 $$c©2022
001446791 300__ $$a1 online resource :$$billustrations (some color).
001446791 336__ $$atext$$btxt$$2rdacontent
001446791 337__ $$acomputer$$bc$$2rdamedia
001446791 338__ $$aonline resource$$bcr$$2rdacarrier
001446791 4901_ $$aEmergence, complexity and computation ;$$vvolume 44
001446791 504__ $$aIncludes bibliographical references and index.
001446791 5050_ $$aPreliminaries -- Enumerating and simulating Turing machines -- The Coding Theorem Method -- Theoretical aspects of nite approximations to Levins semi-measure.
001446791 506__ $$aAccess limited to authorized users.
001446791 520__ $$aThis book explores a different pragmatic approach to algorithmic complexity rooted or motivated by the theoretical foundations of algorithmic probability and explores the relaxation of necessary and sufficient conditions in the pursuit of numerical applicability, with some of these approaches entailing greater risks than others in exchange for greater relevance and applicability. Some established and also novel techniques in the field of applications of algorithmic (Kolmogorov) complexity currently coexist for the first time, ranging from the dominant ones based upon popular statistical lossless compression algorithms (such as LZW) to newer approaches that advance, complement, and also pose their own limitations. Evidence suggesting that these different methods complement each other for different regimes is presented, and despite their many challenges, some of these methods are better grounded in or motivated by the principles of algorithmic information. The authors propose that the field can make greater contributions to science, causation, scientific discovery, networks, and cognition, to mention a few among many fields, instead of remaining either as a technical curiosity of mathematical interest only or as a statistical tool when collapsed into an application of popular lossless compression algorithms. This book goes, thus, beyond popular statistical lossless compression and introduces a different methodological approach to dealing with algorithmic complexity. For example, graph theory and network science are classic subjects in mathematics widely investigated in the twentieth century, transforming research in many fields of science from economy to medicine. However, it has become increasingly clear that the challenge of analyzing these networks cannot be addressed by tools relying solely on statistical methods. Therefore, model-driven approaches are needed. Recent advances in network science suggest that algorithmic information theory could play an increasingly important role in breaking those limits imposed by traditional statistical analysis (entropy or statistical compression) in modeling evolving complex networks or interacting networks. Further progress on this front calls for new techniques for an improved mechanistic understanding of complex systems, thereby calling out for increased interaction between systems science, network theory, and algorithmic information theory, to which this book contributes.
001446791 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed May 27, 2022).
001446791 650_0 $$aComputer algorithms.
001446791 650_0 $$aComputational complexity.
001446791 650_0 $$aData compression (Computer science)
001446791 655_0 $$aElectronic books.
001446791 7001_ $$aSoler Toscano, Fernando,$$eauthor.
001446791 7001_ $$aGauvrit, Nicolas,$$d1972-$$eauthor.
001446791 77608 $$iPrint version: $$z3662649837$$z9783662649831$$w(OCoLC)1294138722
001446791 830_0 $$aEmergence, complexity and computation ;$$v44.
001446791 852__ $$bebk
001446791 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-662-64985-5$$zOnline Access$$91397441.1
001446791 909CO $$ooai:library.usi.edu:1446791$$pGLOBAL_SET
001446791 980__ $$aBIB
001446791 980__ $$aEBOOK
001446791 982__ $$aEbook
001446791 983__ $$aOnline
001446791 994__ $$a92$$bISE