Fair linking mechanisms for resource allocation with correlated player types

The proceeding at: Second International Conference,Networked Systems (NETYS 2014), took place 2014. May 15-17. in Marrakech, Morocco.Resource allocation is one of the most relevant problems in the area of Mechanism Design for computing systems. Devising algorithms capable of providing efficient and fair allocation is the objective of many previous research efforts. Usually, the mechanisms they propose use payments in order to deal with selfishness. Since using payments is undesirable in some contexts, a family of mechanisms without payments is proposed in this paper. These mechanisms extend the Linking Mechanism of Jackson and Sonnenschein introducing a generic concept of fairness with correlated preferences. We prove that these mechanisms have good incentive, fairness, and efficiency properties. To conclude, we provide an algorithm, based on the mechanisms, that could be used in practical computing environments.Publicad

Fair linking mechanisms for resource allocation with correlated player types

Resource allocation is one of the most relevant problems in the area of Mechanism Design for computing systems. Devising algorithms capable of providing efficient and fair allocation is the objective of many previous research efforts. Usually, the mechanisms they propose deal with selfishness by introducing utility transfers or payments. Since using payments is undesirable in some contexts, a family of mechanisms without payments is proposed in this paper. These mechanisms extend the Linking Mechanism of Jackson and Sonnenschein introducing a generic concept of fairness with correlated preferences. We prove that these mechanisms have good incentive, fairness, and efficiency properties. To conclude, we provide an algorithm, based on the mechanisms, that could be used in practical computing environments.Publicad

Achieving reliability and fairness in online task computing environments

Mención Internacional en el título de doctorWe consider online task computing environments such as volunteer computing platforms running on BOINC (e.g., SETI@home) and crowdsourcing platforms such as Amazon Mechanical Turk. We model the computations as an Internet-based task computing system under the masterworker paradigm. A master entity sends tasks across the Internet, to worker entities willing to perform a computational task. Workers execute the tasks, and report back the results, completing the computational round. Unfortunately, workers are untrustworthy and might report an incorrect result. Thus, the first research question we answer in this work is how to design a reliable masterworker task computing system. We capture the workers’ behavior through two realistic models: (1) the “error probability model” which assumes the presence of altruistic workers willing to provide correct results and the presence of troll workers aiming at providing random incorrect results. Both types of workers suffer from an error probability altering their intended response. (2) The “rationality model” which assumes the presence of altruistic workers, always reporting a correct result, the presence of malicious workers always reporting an incorrect result, and the presence of rational workers following a strategy that will maximize their utility (benefit). The rational workers can choose among two strategies: either be honest and report a correct result, or cheat and report an incorrect result. Our two modeling assumptions on the workers’ behavior are supported by an experimental evaluation we have performed on Amazon Mechanical Turk. Given the error probability model, we evaluate two reliability techniques: (1) “voting” and (2) “auditing” in terms of task assignments required and time invested for computing correctly a set of tasks with high probability. Considering the rationality model, we take an evolutionary game theoretic approach and we design mechanisms that eventually achieve a reliable computational platform where the master receives the correct task result with probability one and with minimal auditing cost. The designed mechanisms provide incentives to the rational workers, reinforcing their strategy to a correct behavior, while they are complemented by four reputation schemes that cope with malice. Finally, we also design a mechanism that deals with unresponsive workers by keeping a reputation related to the workers’ response rate. The designed mechanism selects the most reliable and active workers in each computational round. Simulations, among other, depict the trade-off between the master’s cost and the time the system needs to reach a state where the master always receives the correct task result. The second research question we answer in this work concerns the fair and efficient distribution of workers among the masters over multiple computational rounds. Masters with similar tasks are competing for the same set of workers at each computational round. Workers must be assigned to the masters in a fair manner; when the master values a worker’s contribution the most. We consider that a master might have a strategic behavior, declaring a dishonest valuation on a worker in each round, in an attempt to increase its benefit. This strategic behavior from the side of the masters might lead to unfair and inefficient assignments of workers. Applying renown auction mechanisms to solve the problem at hand can be infeasible since monetary payments are required on the side of the masters. Hence, we present an alternative mechanism for fair and efficient distribution of the workers in the presence of strategic masters, without the use of monetary incentives. We show analytically that our designed mechanism guarantees fairness, is socially efficient, and is truthful. Simulations favourably compare our designed mechanism with two benchmark auction mechanisms.This work has been supported by IMDEA Networks Institute and the Spanish Ministry of Education grant FPU2013-03792.Programa Oficial de Doctorado en Ingeniería MatemáticaPresidente: Alberto Tarable.- Secretario: José Antonio Cuesta Ruiz.- Vocal: Juan Julián Merelo Guervó

Individual differences in good manners rather than compassion predict fair allocations of wealth in the dictator game

Objective. One of the most common tools for studying prosociality is the dictator game, in which allocations to one’s partner are often described in terms of altruism. However, there is less consensus regarding the motivations driving these allocations, which may represent either emotional concern for others (compassion), adherence to social norms regarding fairness (politeness), or both. Method. In this paper, we apply personality psychology to the study of behavior in the dictator game, in which we examine the discriminant validity of distinct prosocial constructs from the Big Five and HEXACO models in relation to allocations of wealth. Results. Across four studies (combined N = 798) utilizing both hypothetical and incentivized designs, we found that the politeness—but not compassion—aspect of Big Five agreeableness, as well as HEXACO honesty-humility, uniquely predicted dictator allocations within their respective personality models. Conclusions. These findings contribute to a growing literature indicating that the standard dictator game measures “good manners” or adherence to norms concerning fairness, rather than pure emotional concern or compassionate motives, which have important implications for how this paradigm is used and interpreted in psychological research

Politeness and compassion differentially predict adherence to fairness norms and interventions to norm violations in economic games

Adherence to norms and interventions to norm violations are two important forms of social behaviour modelled in economic games. While both appear to serve a prosocial function, they may represent separate mechanisms corresponding with distinct emotional and psychological antecedents, and thus may be predicted by different personality traits. In this study, we compared adherence to fairness norms in the dictator game with responses to violations of the same norms in third-party punishment and recompensation games with respect to prosocial traits from the Big Five and HEXACO models of personality. The results revealed a pattern of differential relations between prosocial traits and game behaviours. While norm adherence in the dictator game was driven by traits reflecting good manners and non-aggression (i.e., the politeness aspect of Big Five agreeableness and HEXACO honesty-humility), third-party recompensation of victims—and to a lesser extent, punishment of offenders—was uniquely driven by traits reflecting emotional concern for others (the compassion aspect of Big Five agreeableness). These findings demonstrate the discriminant validity between similar prosocial constructs and highlight the different prosocial motivations underlying economic game behaviours