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• W2168025438 abstract "In this paper, the mean-square rate of convergence of temporal-difference learning algorithms is analyzed. The analysis is carried out for the case of discounted cost function associated with a Markov chain with a finite dimensional state-space. Under mild conditions, it is shown that these algorithms converge at the rate O(n/sup -1/2/). The results are illustrated with examples related to random coefficient autoregression models and M/G/1 queues." @default.
• W2168025438 created "2016-06-24" @default.
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• W2168025438 date "2002-01-01" @default.
• W2168025438 modified "2023-09-26" @default.
• W2168025438 title "On the mean-square rate of convergence of temporal-difference learning algorithms" @default.
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• W2168025438 doi "https://doi.org/10.1109/acc.2002.1023226" @default.
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