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020			_a9783030709204
024	7		_a10.1007/978-3-030-70920-4 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQA76.9.A43 _b2021 EB
100			_aFeng, Liang _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9681553
245	0	0	_aOptinformatics in Evolutionary Learning and Optimization _cby Liang Feng, Yaqing Hou, Zexuan Zhu.
250			_aFirst edition 2021
264		1	_aCham _bSpringer International Pulishing _c2021
300			_a1 recurso en línea (VIII, 144 páginas) _b57 ilustraciones, 36 ilustraciones a color
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_aarchivo de texto _bPDF
490	0		_aAdaptation Learning and Optimization _x1867-4542 _v25
490	0		_aIntelligent Technologies and Robotics (SpringerNature-42732)
490	0		_aIntelligent Technologies and Robotics (R0) (SpringerNature-43728)
505	0		_aEvolutionary Learning and Optimization -- The Rise of Optinformatics in Evolutionary Computation -- Knowledge Learning and Transfer in Meta-heuristics -- Knowledge Reuse in The Form of Local Search -- Knowledge Reuse via Transfer Learning from Past Search Experiences -- Optinformatics across Heterogeneous Problem Domains and Solvers -- Potential Research Directions.
520	3		_aThis book provides readers the recent algorithmic advances towards realizing the notion of optinformatics in evolutionary learning and optimization. The book also provides readers a variety of practical applications, including inter-domain learning in vehicle route planning, data-driven techniques for feature engineering in automated machine learning, as well as evolutionary transfer reinforcement learning. Through reading this book, the readers will understand the concept of optinformatics, recent research progresses in this direction, as well as particular algorithm designs and application of optinformatics. Evolutionary algorithms (EAs) are adaptive search approaches that take inspiration from the principles of natural selection and genetics. Due to their efficacy of global search and ease of usage, EAs have been widely deployed to address complex optimization problems occurring in a plethora of real-world domains, including image processing, automation of machine learning, neural architecture search, urban logistics planning, etc. Despite the success enjoyed by EAs, it is worth noting that most existing EA optimizers conduct the evolutionary search process from scratch, ignoring the data that may have been accumulated from different problems solved in the past. However, today, it is well established that real-world problems seldom exist in isolation, such that harnessing the available data from related problems could yield useful information for more efficient problem-solving. Therefore, in recent years, there is an increasing research trend in conducting knowledge learning and data processing along the course of an optimization process, with the goal of achieving accelerated search in conjunction with better solution quality. To this end, the term optinformatics has been coined in the literature as the incorporation of information processing and data mining (i.e., informatics) techniques into the optimization process. The primary market of this book is researchers from both academia and industry, who are working on computational intelligence methods and their applications. This book is also written to be used as a textbook for a postgraduate course in computational intelligence emphasizing methodologies at the intersection of optimization and machine learning.
988			_aSpringer_Robotics_2021
650		7	_2embne _9141162 _aAlgoritmos
700			_aHou, Yaqing _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9681554
700			_aZhu, Zexuan _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9681555
776	0	8	_iPrinted edition: _z9783030709198
776	0	8	_iPrinted edition: _z9783030709211
776	0	8	_iPrinted edition: _z9783030709228
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-70920-4 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE