scholarly journals Optimal Budget-Feasible Mechanisms for Additive Valuations

2020 ◽  
Vol 8 (4) ◽  
pp. 1-15
Author(s):  
Nick Gravin ◽  
Yaonan Jin ◽  
Pinyan Lu ◽  
Chenhao Zhang
Keyword(s):  
2021 ◽  
Vol 16 (6) ◽  
pp. 2014-2030
Author(s):  
Alireza Mohammadi ◽  
Seyyed Alireza Hashemi Golpayegani

In today’s world, crowdsourcing is regarded as an effective strategy to deal with a high volume of small issues whose solutions can have their own complexities in systems. Moreover, requesters are currently providing hundreds of thousands of tasks in online job markets and workers need to perform these tasks to earn money. Thus far, various aspects of crowdsourcing including budget management, mechanism design for price management, forcing workers to behave truthfully in bidding prices, or maximized gains of crowdsourcing have been considered in different studies. One of the main existing challenges in crowdsourcing is how to ensure truthful reporting is provided by contributing workers. Since the amount of pay to workers is directly correlated with the number of tasks performed by them over a period of time, it can be predicted that strong incentives encourage them to carry out more tasks by giving untruthful answers (providing the first possible answer without examining it) in order to increase the amount of pay. However, crowdsourcing requesters need to obtain truthful reporting as an output of tasks assigned to workers. In this study, a mechanism was developed whose implementation in crowdsourcing could ensure truthful reporting by workers. The mechanism provided in this study was evaluated as more budget feasible and it was also fairer for requesters and workers due to its well-defined procedure.


Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 805
Author(s):  
Jia Xu ◽  
Shangshu Yang ◽  
Weifeng Lu ◽  
Lijie Xu ◽  
Dejun Yang

The recent development of human-carried mobile devices has promoted the great development of mobile crowdsensing systems. Most existing mobile crowdsensing systems depend on the crowdsensing service of the deep cloud. With the increasing scale and complexity, there is a tendency to enhance mobile crowdsensing with the edge computing paradigm to reduce latency and computational complexity, and improve the expandability and security. In this paper, we propose an integrated solution to stimulate the strategic users to contribute more for truth discovery in the edge-assisted mobile crowdsensing. We design an incentive mechanism consisting of truth discovery stage and budget feasible reverse auction stage. In truth discovery stage, we estimate the truth for each task in both deep cloud and edge cloud. In budget feasible reverse auction stage, we design a greedy algorithm to select the winners to maximize the quality function under the budget constraint. Through extensive simulations, we demonstrate that the proposed mechanism is computationally efficient, individually rational, truthful, budget feasible and constant approximate. Moreover, the proposed mechanism shows great superiority in terms of estimation precision and expandability.


Algorithmica ◽  
2020 ◽  
Author(s):  
Stefano Leonardi ◽  
Gianpiero Monaco ◽  
Piotr Sankowski ◽  
Qiang Zhang

AbstractMotivated by many practical applications, in this paper we study budget feasible mechanisms with the goal of procuring an independent set of a matroid. More specifically, we are given a matroid $${\mathcal {M}}=(E,{\mathcal {I}})$$ M = ( E , I ) . Each element of the ground set E is controlled by a selfish agent and the cost of the element is private information of the agent itself. A budget limited buyer has additive valuations over the elements of E. The goal is to design an incentive compatible budget feasible mechanism which procures an independent set of the matroid of largest possible value. We also consider the more general case of the pair $${\mathcal {M}}=(E,{\mathcal {I}})$$ M = ( E , I ) satisfying only the hereditary property. This includes matroids as well as matroid intersection. We show that, given a polynomial time deterministic algorithm that returns an $$\alpha $$ α -approximation to the problem of finding a maximum-value independent set in $${\mathcal {M}}$$ M , there exists an individually rational, truthful and budget feasible mechanism which is $$(3\alpha +1)$$ ( 3 α + 1 ) -approximated and runs in polynomial time, thus yielding also a 4-approximation for the special case of matroids.


Author(s):  
Xiang Liu ◽  
Hau Chan ◽  
Minming Li ◽  
Weiwei Wu

In this paper, we consider the problem of designing budget-feasible mechanisms for selecting agents with private costs from various groups to ensure proportional representation, where the minimum proportion of the selected agents from each group is maximized. Depending on agents' membership in the groups, we consider two main models: single group setting where each agent belongs to only one group, and multiple group setting where each agent may belong to multiple groups. We propose novel budget-feasible proportion-representative mechanisms for these models, which can select representative agents from different groups. The proposed mechanisms guarantee theoretical properties of individual rationality, budget-feasibility, truthfulness, and approximation performance on proportional representation.


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