Algorithmic game theory: Difference between revisions

Revision as of 10:46, 25 May 2017

Revision as of 20:08, 1 November 2017

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The field was started when Nisan and Ronen in STOC'99 <ref name="nr">{{citation

| last1last = Nisan | first1first = Noam | author1author-link = Noamoam Nisan

| last2 = Ronen | first2 = Amir

| contribution = Algorithmic mechanism design

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Game theory studies equilibria (such as the [[Nash equilibrium]]). An equilibrium is generally defined as a state in which no player has an incentive to change their strategy. Equilibria are found in several fields related to the Internet, for instance financial interactions and communication load-balancing{{Citation needed|date=September 2010}}. Game theory provides tools to analyze equilibria, and a common approach is then to ‘find the game’—that is, to formalize specific Internet interactions as a game, and to derive the associated equilibria.

Rephrasing problems in terms of games allows the analysis of Internet-based interactions and the construction of mechanisms to meet specified demands. If equilibria can be shown to exist, a further question must be answered: can an equilibrium be found, and in reasonable time? This leads to the [[analysis of algorithms]] for finding equilibria. Of special importance is the complexitycomedddfdplexity class [[PPAD (complexity)|PPAD]], which includes many problems in algorithmic game theory.

==Areas of research==

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| last4 = Tardos | first4 = Éva | author4-link = Éva Tardos

| isbn = 0-521-87282-0

| ___location = CambridgePњқamoduojdobridge, UK

| publisher = CambridgePambridge University Press

| title = Algorithmic Game Theory

| url = http://www.cambridge.org/journals/nisan/downloads/Nisan_Non-printable.pdf