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020 _a9783031302619
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024 7 _a10.1007/978-3-031-30261-9
_2doi
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_2bicssc
072 7 _aCOM014000
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082 0 4 _a004.0151
_223
100 1 _aBilò, Vittorio.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 0 _aCoping with Selfishness in Congestion Games
_h[electronic resource] :
_bAnalysis and Design via LP Duality /
_cby Vittorio Bilò, Cosimo Vinci.
250 _a1st ed. 2023.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2023.
300 _aXV, 186 p. 1 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _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 ofefficient 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).
650 0 _aComputer science.
650 0 _aGame theory.
650 0 _aComputer programming.
650 1 4 _aTheory of Computation.
650 2 4 _aGame Theory.
650 2 4 _aProgramming Techniques.
700 1 _aVinci, Cosimo.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031302602
776 0 8 _iPrinted edition:
_z9783031302626
776 0 8 _iPrinted edition:
_z9783031302633
830 0 _aMonographs in Theoretical Computer Science. An EATCS Series,
_x2193-2069
856 4 0 _uhttps://doi.org/10.1007/978-3-031-30261-9
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
942 _cSPRINGER
999 _c175741
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