Dynamic Pricing Algorithms for Task Allocation in Multi-agent Swarms

Dasgupta, Prithviraj; Hoeing, Matthew

doi:10.1007/978-3-540-85449-4_5

Cited by 6 publications

(4 citation statements)

References 27 publications

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“…Reference [12] investigates the automatic target recognition (ATR) problem in UAV control and proposes a distributed strategy for UAV swarms. Task allocation problem is discussed in [13][14][15][16][17][18] using different methodologies. Some applications of using a UAV swarm to search and destroy targets could be found in [19][20][21][22].…”

Section: Introductionmentioning

confidence: 99%

Modeling and Flocking Consensus Analysis for Large-Scale UAV Swarms

Huang

2013

Mathematical Problems in Engineering

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Recently, distributed coordination control of the unmanned aerial vehicle (UAV) swarms has been a particularly active topic in intelligent system field. In this paper, through understanding the emergent mechanism of the complex system, further research on the flocking and the dynamic characteristic of UAV swarms will be given. Firstly, this paper analyzes the current researches and existent problems of UAV swarms. Afterwards, by the theory of stochastic process and supplemented variables, a differential-integral model is established, converting the system model into Volterra integral equation. The existence and uniqueness of the solution of the system are discussed. Then the flocking control law is given based on artificial potential with system consensus. At last, we analyze the stability of the proposed flocking control algorithm based on the Lyapunov approach and prove that the system in a limited time can converge to the consensus direction of the velocity. Simulation results are provided to verify the conclusion.

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Section: Introductionmentioning

confidence: 99%

Modeling and Flocking Consensus Analysis for Large-Scale UAV Swarms

Huang

2013

Mathematical Problems in Engineering

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“…By optimizing the discount rate, the interests of both the task contractor and the members are more balanced, so as to improve the task completion. Dasgupta and Hoeing (2008) did some researches on the dynamic pricing algorithms for task allocation in multiagent swarms.…”

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confidence: 99%

“Take Photos to Make Money” APP’s Task Pricing

Huang¹,

Du²,

Yao³

et al. 2018

IJEF

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“Take photos to make money” APP is a self-service crowdsourcing platform based on mobile internet, providing enterprises with a variety of business inspection and information collection. Whether the task’s pricing is reasonable is the key to whether APP can play its role effectively. Based on the data of “China Undergraduate Mathematical Contest in Modeling” in 2017 and taking Guangzhou as an example, this paper studies the factors affecting the task pricing and the reasons for the unfinished tasks by using the multiple linear regression model and K-Means clustering analysis, and obtains a new price scheme combining BP neural network and ergodic search algorithm. Compared with the original scheme, not only the completion rate of the new pricing scheme is improved, but also the cost is reduced, which better meets the interests of both members and entrepreneurs.

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“…Our improvements of the sequential auctions are based on real time concepts like EDF, or on reducing the algorithmic complexity with EDFBP method. Hybrid methods, which combine both auction and swarm approaches, has also been introduced by several authors like Zhang et al (2007) or Dasgupta & Hoeing (2008). In all these cases only a single robot can be assigned to the same task (SR scenario).…”

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confidence: 99%