STOC '01 Proceedings of the thirty-third annual ACM symposium on Theory of computing
Journal of the ACM (JACM)
Selfish traffic allocation for server farms
STOC '02 Proceedings of the thiry-fourth annual ACM symposium on Theory of computing
Desiderata for agent argumentation protocols
Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 1
Tight bounds for worst-case equilibria
SODA '02 Proceedings of the thirteenth annual ACM-SIAM symposium on Discrete algorithms
The Structure and Complexity of Nash Equilibria for a Selfish Routing Game
ICALP '02 Proceedings of the 29th International Colloquium on Automata, Languages and Programming
On optimal outcomes of negotiations over resources
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Nashification and the coordination ratio for a selfish routing game
ICALP'03 Proceedings of the 30th international conference on Automata, languages and programming
STACS'99 Proceedings of the 16th annual conference on Theoretical aspects of computer science
Evolutionary equilibrium in Bayesian routing games: Specialization and niche formation
Theoretical Computer Science
Evolutionary equilibrium in Bayesian routing games: specialization and niche formation
ESA'07 Proceedings of the 15th annual European conference on Algorithms
Tradeoffs and Average-Case Equilibria in Selfish Routing
ACM Transactions on Computation Theory (TOCT)
Efficiency analysis of load balancing games with and without activation costs
Journal of Scheduling
Altruism in Atomic Congestion Games
ACM Transactions on Economics and Computation
Theoretical Computer Science
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This paper studies a resource allocation problem introduced by Koutsoupias and Papadimitriou. The scenario is modelled as a multiple-player game in which each player selects one of a finite number of known resources. The cost to the player is the total weight of all players who choose that resource, multiplied by the ''delay'' of that resource. Recent papers have studied the Nash equilibria and social optima of this game in terms of the L"~ cost metric, in which the social cost is taken to be the maximum cost to any player. We study the L"1 variant of this game, in which the social cost is taken to be the sum of the costs to the individual players, rather than the maximum of these costs. We give bounds on the size of the coordination ratio, which is the ratio between the social cost incurred by selfish behavior and the optimal social cost; we also study the algorithmic problem of finding optimal (lowest-cost) assignments and Nash Equilibria. Additionally, we obtain bounds on the ratio between alternative Nash equilibria for some special cases of the problem.