An equilibrium analysis of the probabilistic serial mechanism

Ekici, Özgün; Kesten, Onur

doi:10.1007/s00182-015-0475-9

Cited by 14 publications

(10 citation statements)

References 24 publications

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“…Somewhat surprisingly, the Nash equilibria of the mechanism were only recently studied. Aziz et al [5] prove that the mechanism has pure Nash equilibria while Ekici and Kesten [14] study the ordinal equilibria of the mechanism and prove that the desirable properties of the mechanism are not necessarily satisfied for those profiles.…”

Section: Discussion and Related Workmentioning

confidence: 99%

Social Welfare in One-Sided Matching Mechanisms

Christodoulou

Filos-Ratsikas

Frederiksen

et al. 2016

Autonomous Agents and Multiagent Systems

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We study the Price of Anarchy of mechanisms for the wellknown problem of one-sided matching, or house allocation, with respect to the social welfare objective. We consider both ordinal mechanisms, where agents submit preference lists over the items, and cardinal mechanisms, where agents may submit numerical values for the items being allocated. We present a general lower bound of Ω( √ n) on the Price of Anarchy, which applies to all mechanisms and we show that a very well-known mechanisms, Probabilistic Serial achieves a matching upper bound. We extend our lower bound to the Price of Stability of a large class of mechanisms that satisfy a common proportionality property.

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Section: Discussion and Related Workmentioning

confidence: 99%

Social Welfare in One-Sided Matching Mechanisms

Christodoulou

Filos-Ratsikas

Frederiksen

et al. 2016

Autonomous Agents and Multiagent Systems

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“…Other interesting aspects of PS and RSD such as computational complexity and best-response strategies have also been explored [8,9,19]. In this vein, Aziz et al proved the existence of pure Nash equilibria, but showed that computing Table 5: A random assignment for a preference profile wherein PS and RSD both prescribe an identical matching, i.e.…”

Section: Related Literaturementioning

confidence: 99%

Investigating the characteristics of one-sided matching mechanisms under various preferences and risk attitudes

Hosseini

Larson

Cohen

2018

Auton Agent Multi-Agent Syst

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One-sided matching mechanisms are fundamental for assigning a set of indivisible objects to a set of self-interested agents when monetary transfers are not allowed. Two widely-studied randomized mechanisms in multiagent settings are the Random Serial Dictatorship (RSD) and the Probabilistic Serial Rule (PS). Both mechanisms require only that agents specify ordinal preferences and have a number of desirable economic and computational properties. However, the induced outcomes of the mechanisms are often incomparable and thus there are challenges when it comes to deciding which mechanism to adopt in practice.In this paper, we first consider the space of general ordinal preferences and provide empirical results on the (in)comparability of RSD and PS. We analyze their respective economic properties under general and lexicographic preferences. We then instantiate utility functions with the goal of gaining insights on the manipulability, efficiency, and envyfreeness of the mechanisms under different riskattitude models. Our results hold under various preference distribution models, which further confirm the broad use of RSD in most practical applications.

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“…In fact, many mechanisms, such as CEEI, is manipulable as well. Ekici and Kesten (2016) shows that when agents are not truthful, the outcome of Probabilistic Serial may not satisfy desirable properties related to efficiency and envy-freeness. Hence, researchers look to develop refined analytic and experimental works to answer a basic question: which mechanism to employ in practical applications?…”

Section: Introductionmentioning

confidence: 99%

Bounded Incentives in Manipulating the Probabilistic Serial Rule

Wang

Wei

Zhang

2020

AAAI

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The Probabilistic Serial mechanism is well-known for its desirable fairness and efficiency properties. It is one of the most prominent protocols for the random assignment problem. However, Probabilistic Serial is not incentive-compatible, thereby these desirable properties only hold for the agents' declared preferences, rather than their genuine preferences. A substantial utility gain through strategic behaviors would trigger self-interested agents to manipulate the mechanism and would subvert the very foundation of adopting the mechanism in practice. In this paper, we characterize the extent to which an individual agent can increase its utility by strategic manipulation. We show that the incentive ratio of the mechanism is 3/2. That is, no agent can misreport its preferences such that its utility becomes more than 1.5 times of what it is when reports truthfully. This ratio is a worst-case guarantee by allowing an agent to have complete information about other agents' reports and to figure out the best response strategy even if it is computationally intractable in general. To complement this worst-case study, we further evaluate an agent's utility gain on average by experiments. The experiments show that an agent' incentive in manipulating the rule is very limited. These results shed some light on the robustness of Probabilistic Serial against strategic manipulation, which is one step further than knowing that it is not incentive-compatible.

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An equilibrium analysis of the probabilistic serial mechanism

Cited by 14 publications

References 24 publications

Social Welfare in One-Sided Matching Mechanisms

Social Welfare in One-Sided Matching Mechanisms

Investigating the characteristics of one-sided matching mechanisms under various preferences and risk attitudes

Bounded Incentives in Manipulating the Probabilistic Serial Rule

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