000			03222nam a22004335i 4500
999			_c387126 _d387126
001			387126
003			ES-MaUEC
005			20230214104300.0
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007			cr nn 008mamaa
008			220601s2017 sz | s |||| 0|eng d
020			_a9783031015779
024	7		_a10.1007/978-3-031-01577-9 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQA269 _b2017 EB
100	1		_aFaltings, Boi _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9686631
245	1	0	_aGame Theory for Data Science : _bEliciting Truthful Information _cby Boi Faltings, Goran Radanovic
250			_a1st edition 2017
264		1	_aCham _bSpringer International Publishing _c2017
300			_a1 recurso en línea (XV, 135 páginas)
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aSynthesis Lectures on Artificial Intelligence and Machine Learning _x1939-4616
505	0		_aPreface -- Acknowledgments -- Introduction -- Mechanisms for Verifiable Information -- Parametric Mechanisms for Unverifiable Information -- Nonparametric Mechanisms: Multiple Reports -- Nonparametric Mechanisms: Multiple Tasks -- Prediction Markets: Combining Elicitation and Aggregation -- Agents Motivated by Influence -- Decentralized Machine Learning -- Conclusions -- Bibliography -- Authors' Biographies .
520			_aIntelligent systems often depend on data provided by information agents, for example, sensor data or crowdsourced human computation. Providing accurate and relevant data requires costly effort that agents may not always be willing to provide. Thus, it becomes important not only to verify the correctness of data, but also to provide incentives so that agents that provide high-quality data are rewarded while those that do not are discouraged by low rewards. We cover different settings and the assumptions they admit, including sensing, human computation, peer grading, reviews, and predictions. We survey different incentive mechanisms, including proper scoring rules, prediction markets and peer prediction, Bayesian Truth Serum, Peer Truth Serum, Correlated Agreement, and the settings where each of them would be suitable. As an alternative, we also consider reputation mechanisms. We complement the game-theoretic analysis with practical examples of applications in prediction platforms, community sensing, and peer grading.
988			_aSynthesis Collection of Technology_2017
650		7	_2embne _aTeoría de juegos _9686845
650		7	_2embne _9495511 _aDatos masivos
650		7	_2embne _9166090 _aAprendizaje automático
700	1		_aRadanovic, Goran _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9686632
776	0	8	_iPrinted edition: _z9783031004490
776	0	8	_iPrinted edition: _z9783031027055
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-01577-9 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b02/2023 _dz _esc _zSI