Information rules: a strategic guide to the network economy
Information rules: a strategic guide to the network economy
STOC '01 Proceedings of the thirty-third annual ACM symposium on Theory of computing
Algorithms, games, and the internet
STOC '01 Proceedings of the thirty-third annual ACM symposium on Theory of computing
SIAM Journal on Computing
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
A network pricing game for selfish traffic
Proceedings of the twenty-fourth annual ACM symposium on Principles of distributed computing
Structure and complexity of extreme Nash equilibria
Theoretical Computer Science - Game theory meets theoretical computer science
STACS'99 Proceedings of the 16th annual conference on Theoretical aspects of computer science
The Influence of Link Restrictions on (Random) Selfish Routing
SAGT '08 Proceedings of the 1st International Symposium on Algorithmic Game Theory
Facets of the Fully Mixed Nash Equilibrium Conjecture
SAGT '08 Proceedings of the 1st International Symposium on Algorithmic Game Theory
The structure and complexity of Nash equilibria for a selfish routing game
Theoretical Computer Science
Tradeoffs and average-case equilibria in selfish routing
ESA'07 Proceedings of the 15th annual European conference on Algorithms
Hi-index | 0.00 |
We propose a simple and intuitive cost mechanism which assigns costs for the competitive usage of mresources by n selfish agents. Each agent has an individual demand; demands are drawn according to some probability distribution. The cost paid by an agent for a resource she chooses is the total demand put on the resource divided by the number of agents who chose that same resource. So, resources charge costs in an equitable, fair way, while each resource makes no profit out of the agents. We call our model the Fair Pricing model. Its fair cost mechanism induces a non-cooperative game among the agents. To evaluate the Nash equilibria of this game, we introduce the Diffuse Price of Anarchy, as an extension of the Price of Anarchy that takes into account the probability distribution on the demands. We prove: Pure Nash equilibria may not exist, unless all chosen demands are identical; in contrast, a fully mixed Nash equilibrium exists for all possible choices of the demands. Further on, the fully mixed Nash equilibrium is the unique Nash equilibrium in case there are only two agents. In the worst-case choice of demands, the Price of Anarchy is Θ (n); for the special case of two agents, the Price of Anarchy is less than $2 - \frac{1}{m}$. Assume now that demands are drawn from a bounded, independent probability distribution, where all demands are identically distributed and each is at most a (universal for the class) constant times its expectation. Then, the Diffuse Price of Anarchy is at most that same constant, which is just 2 when each demand is distributed symmetrically around its expectation.