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- W3186333353 abstract "Recently, many cooperative distributed multiagent reinforcement learning (MARL) algorithms have been proposed in the literature. In this work, we study the effect of adversarial attacks on a network that employs a consensus-based MARL algorithm. We show that an adversarial agent can persuade all the other agents in the network to implement policies that optimize an objective that it desires. In this sense, the standard consensus-based MARL algorithms are fragile to attacks." @default.
- W3186333353 created "2021-08-02" @default.
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- W3186333353 date "2021-05-25" @default.
- W3186333353 modified "2023-09-29" @default.
- W3186333353 title "Adversarial attacks in consensus-based multi-agent reinforcement learning" @default.
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- W3186333353 doi "https://doi.org/10.23919/acc50511.2021.9483080" @default.
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