scholarly journals Hedonic Coalition Formation for Distributed Task Allocation among Wireless Agents

2011 ◽  
Vol 10 (9) ◽  
pp. 1327-1344 ◽  
Author(s):  
Walid Saad ◽  
Zhu Han ◽  
Tamer Basar ◽  
Merouane Debbah ◽  
Are Hjorungnes
Keyword(s):  
Coalition Formation ◽  
Task Allocation ◽  
Distributed Task Allocation ◽  
Hedonic Coalition Formation

Distributed Hedonic Coalition Formation for Multi-Robot Task Allocation

2021 ◽  
Author(s):  
Ayan Dutta ◽  
Vladimir Ufimtsev ◽  
Tuffa Said ◽  
Inmo Jang ◽  
Roger Eggen
Keyword(s):  
Coalition Formation ◽  
Task Allocation ◽  
Robot Task ◽  
Hedonic Coalition Formation ◽  
Multi Robot

scholarly journals A multi-responsibility–oriented coalition formation framework for dynamic task allocation in mobile–distributed multi-agent systems

2018 ◽  
Vol 15 (6) ◽  
pp. 172988141881303 ◽  
Author(s):  
Bing Xie ◽  
Xueqiang Gu ◽  
Jing Chen ◽  
LinCheng Shen
Keyword(s):  
Coalition Formation ◽  
Task Allocation ◽  
Game Model ◽  
Multi Agent Systems ◽  
Coalition Game ◽  
Task Execution ◽  
Agent Systems ◽  
Dynamic Task ◽  
Dynamic Task Allocation ◽  
Multi Agent

In this article, we study a problem of dynamic task allocation with multiple agent responsibilities in distributed multi-agent systems. Agents in the research have two responsibilities, communication and task execution. Movements in agent task execution bring changes to the system network structure, which will affect the communication. Thus, agents need to be autonomous on communication network reconstruction for good performance on task execution. First, we analyze the relationships between the two responsibilities of agents. Then, we design a multi-responsibility–oriented coalition formation framework for dynamic task allocation with two parts, namely, task execution and self-adaptation communication. For the former part, we integrate our formerly proposed algorithm in the framework for task execution coalition formation. For the latter part, we develop a constrained Bayesian overlapping coalition game model to formulate the communication network. A task-allocation efficiency–oriented communication coalition utility function is defined to optimize a coalition structure for the constrained Bayesian overlapping coalition game model. Considering the geographical location dependence between the two responsibilities, we define constrained agent strategies to map agent strategies to potential location choices. Based on the abovementioned design, we propose a distributed location pruning self-adaptive algorithm for the constrained Bayesian overlapping coalition formation. Finally, we test the performance of our framework, multi-responsibility–oriented coalition formation framework, with simulation experiments. Experimental results demonstrate that the multi-responsibility oriented coalition formation framework performs better than the other two distributed algorithms on task completion rate (by over 9.4% and over 65% on average, respectively).

Distributed task allocation for multiple heterogeneous UAVs based on consensus algorithm and online cooperative strategy

2018 ◽  
Vol 90 (9) ◽  
pp. 1464-1473 ◽  
Author(s):  
Weinan Wu ◽  
Naigang Cui ◽  
Wenzhao Shan ◽  
Xiaogang Wang
Keyword(s):  
Task Allocation ◽  
Consensus Algorithm ◽  
Communication Link ◽  
Communication Mode ◽  
Cooperative Strategy ◽  
Bayesian Theorem ◽  
Content Type ◽  
Distributed Framework ◽  
Allocation Process ◽  
Distributed Task Allocation

Purpose The purpose of this paper is to develop a distributed task allocation method for cooperative mission planning of multiple heterogeneous unmanned aerial vehicles (UAVs) based on the consensus algorithm and the online cooperative strategy. Design/methodology/approach In this paper, the allocation process is conducted in a distributed framework. The cooperative task allocation problem is proposed with constraints and uncertainties in a real mission. The algorithm based on the consensus algorithm and the online cooperative strategy is proposed for this problem. The local chain communication mode is adopted to restrict the bandwidth of the communication link among the UAVs, and two simulation tests are given to test the optimality and rapidity of the proposed algorithm. Findings This method can handle both continuous and discrete uncertainties in the mission space, and the proposed algorithm can obtain a feasible solution in allowable time. Research limitations/implications This study is only applied to the case that the total number of the UAVs is less than 15. Practical implications This study is expected to be practical for a real mission with uncertain targets. Originality/value The proposed algorithm can go beyond previous works that only deal with continuous uncertainties, and the Bayesian theorem is adopted for estimation of the target.

Reputation-aware Hedonic Coalition Formation for Efficient Serverless Hierarchical Federated Learning

2021 ◽  
pp. 1-1
Author(s):  
Jer Shyuan Ng ◽  
Wei Yang Bryan Lim ◽  
Zehui Xiong ◽  
Xianbin Cao ◽  
Jiangming Jin ◽  
...  
Keyword(s):  
Coalition Formation ◽  
Hedonic Coalition Formation
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