Algorithmic Game Theory: Second International Symposium, by Dov Monderer (auth.), Marios Mavronicolas, Vicky G.

By Dov Monderer (auth.), Marios Mavronicolas, Vicky G. Papadopoulou (eds.)

This ebook constitutes the refereed court cases of the second one overseas Symposium on Algorithmic online game idea, SAGT 2009, held in Paphos, Cyprus, in October 2009.

The 29 revised complete papes provided including three invited lectures have been conscientiously reviewed and chosen from fifty five submissions. The papers are meant to hide all very important components equivalent to resolution ideas, video game sessions, computation of equilibria and industry equilibria, algorithmic mechanism layout, automatic mechanism layout, convergence and studying in video games, complexity periods in video game idea, algorithmic facets of fixed-point theorems, mechanisms, incentives and coalitions, cost-sharing algorithms, computational difficulties in economics, finance, choice concept and pricing, computational social selection, public sale algorithms, cost of anarchy and its family, representations of video games and their complexity, fiscal facets of allotted computing and the web, congestion, routing and community layout and formation video games and game-theoretic methods to networking problems.

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Extra resources for Algorithmic Game Theory: Second International Symposium, SAGT 2009, Paphos, Cyprus, October 18-20, 2009. Proceedings

Example text

Each agent i incurs a cost costi (a, b) = costi (o(a, b)), which depends on her private data and the outcome chosen by the mechanism. To compensate the agents for these costs, the mechanism makes a payment Pi (a, b) to each agent i, which depends on the bids. The objective of every agent i is to maximize her profit given by profiti (a, b) = Pi (a, b) − costi (a, b). As mentioned earlier, we assume the cost functions of the agents to have a special form: The outcome function o assigns an amount wi (a, b) = wi (o(a, b)) of load or work to each agent i and the cost of i is costi (a, b) = αi ·wi (a, b)+βi .

Truthful approximation schemes for single-parameter agents. In: FOCS 2008 (2008) 5. : Limitations of vcg-based mechanisms. Preliminary version in STOC 2007 (2007) 6. : On characterizations of truthful mechanisms for combinatorial auctions and scheduling. In: EC 2008 (2008) 7. : Towards a characterization of truthful combinatorial auctions. In: FOCS 2003 (2003) 8. : Two simplified proofs for roberts theorem. Social Choice and Welfare (2009) 9. : Truth revelation in approximately efficient combinatorial auctions.

Proposition 2). Under this assumption, the situation fits into the framework of mechanism design with one-parameter agents: The agents are the edges, and the private value of edge e ∈ E is its per unit cost te . The selfish behavior of the network users is taken into account by considering Nash flows. Corollary 2 states that the load on an edge of the network cannot increase when the toll on the edge is increased, so the algorithm described above, which just takes the Nash flow with the given latencies and the tolls defined by the edges as the assignment of load to the edges, is a monotone algorithm.

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