Coalition formation with non-transferable payoff for group buying

Author(s):  
Frederick Asselin ◽  
Brahim Chaib-draa
Author(s):  
Lang Ruan ◽  
Jin Chen ◽  
Qiuju Guo ◽  
Xiaobo Zhang ◽  
Yuli Zhang ◽  
...  

In scenarios such as natural disasters and military strike, it is common for unmanned aerial vehicles (UAVs) to form groups to execute reconnaissance and surveillance. To ensure the effectiveness of UAV communications, repeated resource acquisition issues and transmission mechanism design need to be addressed urgently. In this paper, we build an information interaction scenario in a Flying Ad-hoc network (FANET). The data transmission problem with the goal of throughput maximization is modeled as a coalition game framework. Then, a novel mechanism of coalition selection and data transmission based on group-buying is investigated. Since large-scale UAVs will generate high transmission overhead due to the overlapping resource requirements, we propose a resource allocation optimization method based on distributed data content. Comparing existing works, a data transmission and coalition formation mechanism is designed. Then the system model is classified into graph game and coalition formation game. Through the design of the utility function, we prove that both games have stable solutions. We also prove the convergence of the proposed approach with coalition order and Pareto order. Binary log-linear learning based coalition selection algorithm (BLL-CSA) is proposed to explore the stable coalition partition of system model. Simulation results show that the proposed data transmission and coalition formation mechanism can achieve higher data throughput than the other contrast algorithms.


2010 ◽  
Vol 49 (1) ◽  
pp. 1-13 ◽  
Author(s):  
Cuihong Li ◽  
Katia Sycara ◽  
Alan Scheller-Wolf

2004 ◽  
Vol 3 (4) ◽  
pp. 341-354 ◽  
Author(s):  
Cuihong Li ◽  
Shuchi Chawla ◽  
Uday Rajan ◽  
Katia Sycara

2011 ◽  
Vol 14 (02) ◽  
pp. 111-131 ◽  
Author(s):  
FRANK E. WALTER

Despite the fact that social networks are ubiquitous on the Internet, only few websites exploit the potential of combining user communities and online marketplaces. Not many platforms allow users to engage in a phenomenon called "group buying" — buyers joining groups, or coalitions, to bundle their purchasing power towards sellers. We argue that this may be due to a lack of face-to-face interaction on the Internet; often, users do not know which other users to trust, which makes them suspicious of engaging in online business, in particular if many unknown other parties are involved. This situation, however, can be alleviated by leveraging the social networks of users: based on who a user knows and is connected to, a trust metric — for example, the TrustWebRank metric developed by us — can be computed to assess who else may be considered trustworthy to that user. In this paper, we build a simple agent-based model of coalition formation among agents in the setting of group buying in an electronic marketplace. In this model, agents use their trust relationships in order to determine who to form coalitions with. We show that this leads agents to experience high utility and that agents are able to learn who is trustworthy and who is not, even when they have no initial knowledge about the trustworthiness of other agents. This work may provide the foundation for a real-world application of an online coalition formation platform for e-commerce built on a social networking platform such as Facebook.


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