The concepts of [[price of anarchy]] and [[price of stability]] were introduced to capture the loss in performance of a system due to the selfish behavior of its participants. The [[price of anarchy]] captures the worst-case performance of the system at equilibrium relative to the optimal performance possible.<ref>{{cite book | authorsauthor1=[[Tim Roughgarden]] |title=Selfish routing and the price of anarchy |publisher=[[MIT Press]] |year=2005 |isbn=0-262-18243-2 }}</ref> The [[price of stability]], on the other hand, captures the relative performance of the best equilibrium of the system.<ref>*{{Cite journal|first1=Elliot|last1=Anshelevich|first2=Anirban|last2=Dasgupta|first3=Jon|last3=Kleinberg|first4=Éva|last4=Tardos|first5=Tom|last5=Wexler|first6=Tim|last6=Roughgarden|title=The Price of Stability for Network Design with Fair Cost Allocation|journal=SIAM J. Comput.|volume=38|issue=4|year=2008|pages=1602–1623|doi=10.1137/070680096}}</ref> These concepts are counterparts to the notion of [[approximation ratio]] in algorithm design.
===Complexity of finding equilibria===
Line 85:
* [[Multi-agent systems]]
And the area counts with diverse practical applications:<ref>{{cite book | authorsauthor1=[[Tim Roughgarden]] |title=Twenty lectures on algorithmic game theory |publisher=[[Cambridge University Press]] |year=2016 |isbn=9781316624791}}</ref><ref>{{cite web | url=http://www.sigecom.org/ec19/callforpapers.html |title = EC'19 || 20th ACM Conference on Economics and Computation}}</ref>
