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- W4309818899 abstract "A cooperative game theory framework is proposed to solve multi-robot task allocation (MRTA) problems. In particular, a cooperative game is built to assess the performance of sets of robots and tasks so that the Shapley value of the game can be used to compute their average marginal contribution. This fact allows us to partition the initial MRTA problem into a set of smaller and simpler MRTA subproblems, which are formed by ranking and clustering robots and tasks according to their Shapley value. A large-scale simulation case study illustrates the benefits of the proposed scheme, which is assessed using a genetic algorithm (GA) as a baseline method. The results show that the game theoretical approach outperforms GA both in performance and computation time for a range of problem instances." @default.
- W4309818899 created "2022-11-29" @default.
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- W4309818899 date "2023-03-01" @default.
- W4309818899 modified "2023-10-16" @default.
- W4309818899 title "Multi-robot task allocation clustering based on game theory" @default.
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- W4309818899 doi "https://doi.org/10.1016/j.robot.2022.104314" @default.
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