17,651 research outputs found

    Utilitarian resource assignment

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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 LāˆžL_\infty cost metric, in which the social cost is taken to be the maximum cost to any player. We study the L1L_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.Comment: 19 page

    Efficiency analysis of load balancing games with and without activation costs

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    In this paper, we study two models of resource allocation games: the classical load-balancing game and its new variant involving resource activation costs. The resources we consider are identical and the social costs of the games are utilitarian, which are the average of all individual players' costs. Using the social costs we assess the quality of pure Nash equilibria in terms of the price of anarchy (PoA) and the price of stability (PoS). For each game problem, we identify suitable problem parameters and provide a parametric bound on the PoA and the PoS. In the case of the load-balancing game, the parametric bounds we provide are sharp and asymptotically tight

    The Complexity of Fully Proportional Representation for Single-Crossing Electorates

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    We study the complexity of winner determination in single-crossing elections under two classic fully proportional representation rules---Chamberlin--Courant's rule and Monroe's rule. Winner determination for these rules is known to be NP-hard for unrestricted preferences. We show that for single-crossing preferences this problem admits a polynomial-time algorithm for Chamberlin--Courant's rule, but remains NP-hard for Monroe's rule. Our algorithm for Chamberlin--Courant's rule can be modified to work for elections with bounded single-crossing width. To circumvent the hardness result for Monroe's rule, we consider single-crossing elections that satisfy an additional constraint, namely, ones where each candidate is ranked first by at least one voter (such elections are called narcissistic). For single-crossing narcissistic elections, we provide an efficient algorithm for the egalitarian version of Monroe's rule.Comment: 23 page

    Serve or Skip: The Power of Rejection in Online Bottleneck Matching

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    We consider the online matching problem, where n server-vertices lie in a metric space and n request-vertices that arrive over time each must immediately be permanently assigned to a server-vertex.We focus on the egalitarian bottleneck objective, where the goal is to minimize the maximum distance between any request and its server. It has been demonstrated that while there are effective algorithms for the utilitarian objective (minimizing total cost) in the resource augmentation setting where the offline adversary has half the resources, these are not effective for the egalitarian objective. Thus, we propose a new Serve-or-Skip bicriteria analysis model, where the online algorithm may reject or skip up to a specified number of requests, and propose two greedy algorithms: GRI NN(t) and GRIN(t) . We show that the Serve-or-Skip model of resource augmentation analysis can essentially simulate the doubled-server capacity model, and then examine the performance of GRI NN(t) and GRIN(t)

    Towards an empirical analysis of justice in ecosystem governance

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    The 2010 Nagoya Protocol under the Convention on Biological Diversity and recent changes in the policies of major international conservation organizations highlight current interest in revisiting the moral case for conservation. Concerns with equity and human rights challenge well-established notions of justice centered on human responsibility toward nature, the common good or the rights of future generations. This review introduces an empirical approach to the analysis of justice and shows how conservation scientists can apply it to ecosystem services-based governance (or in short, ecosystem governance). It identifies dominant notions of justice and points out their compatibility with utilitarian theories of justice. It then discusses the limited appropriateness of these notions in many contexts in which conservation takes place in the Global South and explores how technical components of ecosystem governance influence the realization of the notions in practice. The review highlights the need for conservation scientists and managers to analyze the justice of ecosystem governance in addition to their effectiveness and efficiency. Justice offers a more encompassing perspective than equity for the empirical analysis of conservation governance

    Reallocation Problems in Agent Societies: A Local Mechanism to Maximize Social Welfare

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    Resource reallocation problems are common in real life and therefore gain an increasing interest in Computer Science and Economics. Such problems consider agents living in a society and negotiating their resources with each other in order to improve the welfare of the population. In many studies however, the unrealistic context considered, where agents have a flawless knowledge and unlimited interaction abilities, impedes the application of these techniques in real life problematics. In this paper, we study how agents should behave in order to maximize the welfare of the society. We propose a multi-agent method based on autonomous agents endowed with a local knowledge and local interactions. Our approach features a more realistic environment based on social networks, inside which we provide the behavior for the agents and the negotiation settings required for them to lead the negotiation processes towards socially optimal allocations. We prove that bilateral transactions of restricted cardinality are sufficient in practice to converge towards an optimal solution for different social objectives. An experimental study supports our claims and highlights the impact of a realistic environment on the efficiency of the techniques utilized.Resource Allocation, Negotiation, Social Welfare, Agent Society, Behavior, Emergence

    A Comparison of Optimal Tax Policies when Compensation or Responsibility Matter

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    This paper examines optimal redistribution in a model with high- and low-skilled individuals with heterogeneous tastes for labor. We compare the extent to which optimal policies based on different normative criteria obey the principles of compensation (for differential skills) and responsibility (for preferences for labor) when labor supply is along the extensive margin. With heterogeneity in skills and preferences, traditional Welfarist criteria including Utilitarianism present unappealing policy recommendations in some scenarios as they fail to take compensation and responsibility issues into account. Criteria from the social choice literature perform better in this regard in first-and second-best. More importantly, these equality of opportunity criteria push the second-best policy away from an Earned Income Tax Credit and in the direction of a Negative Income Tax.optimal income taxation, equality of opportunity, heterogeneous preferences for labor
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