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008			230510s2023 sz | o |||| 0|eng d
020			_a9783031302619
024	7		_a10.1007/978-3-031-30261-9 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQA269 _b2023 EB
100	1		_aBilò, Vittorio _eautor _4http://id.loc.gov/vocabulary/relators/aut _9689473
245	1	0	_aCoping with Selfishness in Congestion Games : _bAnalysis and Design via LP Duality _cby Vittorio Bilò, Cosimo Vinci
250			_a1st ed 2023
264		1	_aCham _bSpringer International Publishing _c2023
300			_a1 recurso en línea
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	0		_aMonographs in Theoretical Computer Science An EATCS Series _x2193-2069
505	0		_aPart I, Coping with Selfishness in Congestion Games: Introduction -- Part II, Analysis of the Performance of Congestion Games -- Part III, How to Improve the Performance of Congestion Games via Taxes -- Part IV, Other Strategies to Improve the Performance of Congestion Games. .
520			_aCongestion games constitute perhaps the most significant class of non-cooperative games because of their effectiveness in modeling several real scenarios. Since the advent of algorithmic game theory, characterizing the inefficiency of selfish behavior in these games, as well as defining good strategies to reduce it (in the same spirit of approximation and online algorithms' design), have stood as fundamental challenges. This unique volume shows how these challenges can be addressed productively via linear programming and duality theory. In particular, the volume: Measures the efficiency of selfish behavior in several classes of congestion games Demonstrates how this efficiency changes when considering different solution concepts, different types of latency functions (from linear and polynomial, to very general ones) and different combinatorial properties of the players' strategies (e.g., singleton strategies) Covers the analysis and design of efficient online algorithms for machine scheduling and load balancing problems Utilises taxation mechanisms and Stackelberg strategies to improve the efficiency of selfish behavior, revealing that the performance of the proposed mechanisms is best possible within the considered category Formulates results based on the application of the primal-dual method-a powerful tool suited to prove good bounds on the performance guarantee of self-emerging solutions in congestion games This book is suitable for PhD (or master's degree) students and researchers working in algorithmic game theory. In particular, it may serve as reference guide for those interested in deepening their knowledge on the fascinating field of the price of anarchy in congestion games and related topics. Vittorio Bilò is Associate Professor at the Department of Mathematics and Physics "Ennio De Giorgi" in University of Salento (Lecce, Italy). Cosimo Vinci is Assistant Professor at the Department of Information Engineering, Electrical Engineering and Applied Mathematics in University of Salerno (Fisciano, Italy).
988			_aSpringer_Computer_2023
650		7	_2embne _9686845 _aTeoría de juegos
700	1		_9689474 _aVinci, Cosimo _eautor
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-30261-9 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b01/2024 _dz _eb _zSI