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- W2102473090 abstract "This paper presents a reinforcement learning algorithm used to allocate tasks to agents in an uncertain real-time environment. In such environment, tasks have to be analyzed and allocated really fast for the multiagent system to be effective. To analyze those tasks, described by a lot of attributes, we have used a selective perception technique to enable agents to narrow down the description of each task, enabling the reinforcement learning algorithm to work on a problem with a reasonable number of possible states." @default.
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- W2102473090 date "2004-07-19" @default.
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- W2102473090 title "From Global Selective Perception to Local Selective Perception" @default.
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- W2102473090 doi "https://doi.org/10.1109/aamas.2004.130" @default.
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