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A Task-Driven Multi-UAV Coalition Formation Mechanism
Computer Science and Game Theory · Submitted 8 Mar 2024
abstract compiled · 2026-09-23 · no language-model review
The authors' main claim Finally, experimental results demonstrated that the proposed algorithm, compared to currently classical algorithms, not only forms more stable coalitions but also further enhances the overall utility of coalitions effectively.
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The abstract, sentence by sentence
With the rapid advancement of UAV technology, the problem of UAV coalition formation has become a hotspot. Therefore, designing task-driven multi-UAV coalition formation mechanism has become a challenging problem. However, existing coalition formation mechanisms suffer from low relevance between UAVs and task requirements, resulting in overall low coalition utility and unstable coalition structures. To address these problems, this paper proposed a novel multi-UAV coalition network collaborative task completion model, considering both coalition work capacity and task-requirement relationships. This model stimulated the formation of coalitions that match task requirements by using a revenue function based on the coalition's revenue threshold. Subsequently, an algorithm for coalition formation based on marginal utility was proposed. Specifically, the algorithm utilized Shapley value to achieve fair utility distribution within the coalition, evaluated coalition values based on marginal utility preference order, and achieved stable coalition partition through a limited number of iterations. Additionally, we theoretically proved that this algorithm has Nash equilibrium solution. Finally, experimental results demonstrated that the proposed algorithm, compared to currently classical algorithms, not only forms more stable coalitions but also further enhances the overall utility of coalitions effectively.
background contribution method result interpretation main claim
| # | sentence | role | the authors' own work | states the main conclusion | strength |
|---|---|---|---|---|---|
| s0 | With the rapid advancement of UAV technology, the problem of UAV coalition formation has become a hotspot. | background 1.00 | 0.04 | 0.01 | asserted 1.00 |
| s1 | Therefore, designing task-driven multi-UAV coalition formation mechanism has become a challenging problem. | background 0.93 | 0.05 | 0.02 | asserted 1.00 |
| s2 | However, existing coalition formation mechanisms suffer from low relevance between UAVs and task requirements, resulting in overall low coalition utility and unstable coalition structures. | gap 0.92 | 0.04 | 0.02 | asserted 1.00 |
| s3 | To address these problems, this paper proposed a novel multi-UAV coalition network collaborative task completion model, considering both coalition work capacity and task-requirement relationships. | contribution 0.84 | 0.91 | 0.08 | asserted 1.00 |
| s4 | This model stimulated the formation of coalitions that match task requirements by using a revenue function based on the coalition's revenue threshold. | method 0.97 | 0.90 | 0.05 | asserted 1.00 |
| s5 | Subsequently, an algorithm for coalition formation based on marginal utility was proposed. | method 0.84 | 0.92 | 0.03 | asserted 0.99 |
| s6 | Specifically, the algorithm utilized Shapley value to achieve fair utility distribution within the coalition, evaluated coalition values based on marginal utility preference order, and achieved stable coalition partition through a limited number of iterations. | method 0.99 | 0.93 | 0.06 | asserted 1.00 |
| s7 | Additionally, we theoretically proved that this algorithm has Nash equilibrium solution. | contribution 0.61 | 0.95 | 0.07 | asserted 1.00 |
| s8 | Finally, experimental results demonstrated that the proposed algorithm, compared to currently classical algorithms, not only forms more stable coalitions but also further enhances the overall utility of coalitions effectively. | result 0.99 | 0.96 | 0.87 | asserted 1.00 |
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The paper
Original abstract
With the rapid advancement of UAV technology, the problem of UAV coalition formation has become a hotspot. Therefore, designing task-driven multi-UAV coalition formation mechanism has become a challenging problem. However, existing coalition formation mechanisms suffer from low relevance between UAVs and task requirements, resulting in overall low coalition utility and unstable coalition structures. To address these problems, this paper proposed a novel multi-UAV coalition network collaborative task completion model, considering both coalition work capacity and task-requirement relationships. This model stimulated the formation of coalitions that match task requirements by using a revenue function based on the coalition's revenue threshold. Subsequently, an algorithm for coalition formation based on marginal utility was proposed. Specifically, the algorithm utilized Shapley value to achieve fair utility distribution within the coalition, evaluated coalition values based on marginal utility preference order, and achieved stable coalition partition through a limited number of iterations. Additionally, we theoretically proved that this algorithm has Nash equilibrium solution. Finally, experimental results demonstrated that the proposed algorithm, compared to currently classical algorithms, not only forms more stable coalitions but also further enhances the overall utility of coalitions effectively.
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