Conference
Algorithmic Game Theory
About: Algorithmic Game Theory is an academic conference. The conference publishes majorly in the area(s): Nash equilibrium & Price of anarchy. Over the lifetime, 407 publications have been published by the conference receiving 5590 citations.
Papers published on a yearly basis
Papers
1 Sep 2007
TL;DR: In this article, the authors give an introduction to the micro-economic field of Mechanism Design, a subfield of economic theory that is rather unique within economics in having an engineering perspective, and view the goals of the designed mechanisms in the very abstract terms of social choice.
Abstract: We give an introduction to the micro-economic field of Mechanism Design slightly biased toward a computer-scientist's point of view. Introduction Mechanism Design is a subfield of economic theory that is rather unique within economics in having an engineering perspective. It is interested in designing economic mechanisms, just like computer scientists are interested in designing algorithms, protocols, or systems. It is best to view the goals of the designed mechanisms in the very abstract terms of social choice . A social choice is simply an aggregation of the preferences of the different participants toward a single joint decision. Mechanism Design attempts implementing desired social choices in a strategic setting – assuming that the different members of society each act rationally in a game theoretic sense. Such strategic design is necessary since usually the preferences of the participants are private. This high-level abstraction of aggregation of preferences may be seen as a common generalization of a multitude of scenarios in economics as well as in other social settings such as political science. Here are some basic classic examples: Elections : In political elections each voter has his own preferences between the different candidates, and the outcome of the elections is a single social choice. Markets : Classical economic theory usually assumes the existence and functioning of a “perfect market.” In reality, of course, we have only interactions between people, governed by some protocols. Each participant in such an interaction has his own preferences, but the outcome is a single social choice: the reallocation of goods and money. […]
384 citations
17 Oct 2011
TL;DR: In this paper, the authors consider the many-to-one matching market where peer effects are derived from an underlying social network and show that stable matchings always exist and characterize the set of stable matching in terms of social welfare.
Abstract: Many-to-one matching markets exist in numerous different forms, such as college admissions, matching medical interns to hospitals for residencies, assigning housing to college students, and the classic firms and workers market. In all these markets, externalities such as complementarities and peer effects severely complicate the preference ordering of each agent. Further, research has shown that externalities lead to serious problems for market stability and for developing efficient algorithms to find stable matchings. In this paper we make the observation that peer effects are often the result of underlying social connections, and we explore a formulation of the many-to-one matching market where peer effects are derived from an underlying social network. The key feature of our model is that it captures peer effects and complementarities using utility functions, rather than traditional preference ordering. With this model and considering a weaker notion of stability, namely twosided exchange stability, we prove that stable matchings always exist and characterize the set of stable matchings in terms of social welfare. To characterize the efficiency of matching markets with externalities, we provide general bounds on how far the welfare of the worst-case stable matching can be from the welfare of the optimal matching, and find that the structure of the social network (e.g. how well clustered the network is) plays a large role.
271 citations
13 Oct 2009
TL;DR: This work considers the computation of optimal Stackelberg strategies in general two-player Bayesian games, given that all the payoffs and the prior distribution over types are known.
Abstract: Computing optimal Stackelberg strategies in general two-player Bayesian games (not to be confused with Stackelberg strategies in routing games) is a topic that has recently been gaining attention, due to their application in various security and law enforcement scenarios. Earlier results consider the computation of optimal Stackelberg strategies, given that all the payoffs and the prior distribution over types are known. We extend these results in two different ways. First, we consider learning optimal Stackelberg strategies. Our results here are mostly positive. Second, we consider computing approximately optimal Stackelberg strategies. Our results here are mostly negative.
176 citations
13 Oct 2009
TL;DR: A detailed algorithmic study of the cost of stability in weighted voting games, a simple but expressive class of games which can model decision-making in political bodies, and cooperation in multiagent settings is provided.
Abstract: A key question in cooperative game theory is that of coalitional stability, usually captured by the notion of the core --the set of outcomes such that no subgroup of players has an incentive to deviate. However, some coalitional games have empty cores, and any outcome in such a game is unstable.
In this paper, we investigate the possibility of stabilizing a coalitional game by using external payments. We consider a scenario where an external party, which is interested in having the players work together, offers a supplemental payment to the grand coalition (or, more generally, a particular coalition structure). This payment is conditional on players not deviating from their coalition(s). The sum of this payment plus the actual gains of the coalition(s) may then be divided among the agents so as to promote stability. We define the cost of stability (CoS) as the minimal external payment that stabilizes the game.
We provide general bounds on the cost of stability in several classes of games, and explore its algorithmic properties. To develop a better intuition for the concepts we introduce, we provide a detailed algorithmic study of the cost of stability in weighted voting games, a simple but expressive class of games which can model decision-making in political bodies, and cooperation in multiagent settings. Finally, we extend our model and results to games with coalition structures.
128 citations
1 Jul 2011
TL;DR: It turns out that Nash flows over time can be seen as a concatenation of special static flows, so the underlying flow over time model is the so-called deterministic queuing model that is very popular in road traffic simulation and related fields.
Abstract: We study Nash equilibria in the context of flows over time. Many results on static routing games have been obtained over the last ten years. In flows over time (also called dynamic flows), flow travels through a network over time and, as a consequence, flow values on edges are time-dependent. This more realistic setting has not been tackled from the viewpoint of algorithmic game theory yet; but there is a rich literature on game theoretic aspects of flows over time in the traffic community.
We present a novel characterization of Nash equilibria for flows over time. It turns out that Nash flows over time can be seen as a concatenation of special static flows. The underlying flow over time model is the so-called deterministic queuing model that is very popular in road traffic simulation and related fields. Based upon this, we prove the first known results on the price of anarchy for flows over time.
126 citations
Performance Metrics
| Year | Papers |
|---|---|
| 2023 | 1 |
| 2022 | 24 |
| 2021 | 27 |
| 2020 | 23 |
| 2019 | 26 |
| 2018 | 26 |