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- W3040014827 abstract "We present a method of supervised learning from demonstration for real-time, online training of complex heterogenous multiagent behaviors which scale to large numbers of agents in operation. Our learning method is applicable in domains where coordinated behaviors must be created quickly in unexplored environments. Examples of such problem domains includes disaster relief, search and rescue, and gaming environments. We demonstrate this training method in an adversarial mining scenario which coordinates four types of individual agents to perform six distinct roles in a mining task." @default.
- W3040014827 created "2020-07-10" @default.
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- W3040014827 date "2020-01-01" @default.
- W3040014827 modified "2023-09-24" @default.
- W3040014827 title "Scalable Heterogeneous Multiagent Learning from Demonstration" @default.
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- W3040014827 doi "https://doi.org/10.1007/978-3-030-49778-1_21" @default.
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