Threshold probability of non-terminal type in finite horizon Markov decision processes

Akifumi Kira, Takayuki Ueno, Toshiharu Fujita

研究成果: Article査読

9 被引用数 (Scopus)

抄録

We consider a class of problems concerned with maximizing probabilities, given stage-wise targets, which generalizes the standard threshold probability problem in Markov decision processes. The objective function is the probability that, at all stages, the associatively combined accumulation of rewards earned up to that point takes its value in a specified stage-wise interval. It is shown that this class reduces to the case of the nonnegative-valued multiplicative criterion through an invariant imbedding technique. We derive a recursive formula for the optimal value function and an effective method for obtaining the optimal policies.

本文言語English
ページ(範囲)461-472
ページ数12
ジャーナルJournal of Mathematical Analysis and Applications
386
1
DOI
出版ステータスPublished - 2012 2月 1

ASJC Scopus subject areas

  • 分析
  • 応用数学

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