研究者業績

來島 愛子

Kurushima Aiko

基本情報

所属
上智大学 経済学部経済学科 教授
学位
学士(工学)(東京大学)
修士(工学)(東京大学)
博士(学術)(東京大学)

研究者番号
30408728
J-GLOBAL ID
200901063797881597
researchmap会員ID
6000005085

研究分野

 1

論文

 9
  • 王 琦, 來島愛子, 堀口正之
    京都大学数理解析研究所講究録 196-207 2024年1月  
  • 阪口 昌彦, 來島 愛子, 堀口 正之
    京都大学数理解析研究所講究録2220「不確実環境下における意思決定数理の新展開」 2220 74-81 2022年7月  
  • Xin Guo, Aiko Kurushima, Alexey Piunovskiy, Yi Zhang
    Advances in Applied Probability 53(2) 301-334 2021年6月  
    We consider a gradual-impulse control problem of continuous-time Markov decision processes, where the system performance is measured by the expectation of the exponential utility of the total cost. We show, under natural conditions on the system primitives, the existence of a deterministic stationary optimal policy out of a more general class of policies that allow multiple simultaneous impulses, randomized selection of impulses with random effects, and accumulation of jumps. After characterizing the value function using the optimality equation, we reduce the gradual-impulse control problem to an equivalent simple discrete-time Markov decision process, whose action space is the union of the sets of gradual and impulsive actions.
  • A. Kurushima, A. Piunovskiy, Y. Zhang
    Theory of Probability and its Applications 62(2) 328-334 2018年  査読有り
    In this paper, we present a new monotone approximation of a given real-valued Carathéodory function on the product X × A of Borel spaces, where A is also compact. We demonstrate its application by providing a self-contained and elementary proof of a result of A. Nowak in discrete-time Markov decision processes.
  • A.Kurushima, A.Piunovskiy, Y.Zhang
    Teor. Veroyatnost. i Primenen. 62(2) 405-414 2017年  査読有り
  • Aiko Kurushima, Katsunori Ano
    Mathematica Applicanda 44(1) 209-220 2016年  査読有り
  • Aiko Kurushima, Katsunori Ano
    JOURNAL OF APPLIED PROBABILITY 46(2) 402-414 2009年6月  
    Suppose that an unknown number of objects arrive sequentially according to a Poisson process with random intensity lambda on some fixed time interval [0, T]. We assume a gamma prior density G(lambda)(r, 1/a) for lambda. Furthermore, we suppose that all arriving objects can be ranked uniquely among all preceding arrivals. Exactly one object can be selected. Our aim is to find a stopping time (selection time) which maximizes the time during which the selected object will stay relatively best. Our main result is the following. It is optimal to select the ith object that is relatively best and arrives at some time s(i)((r)) onwards. The value of s(i)((r)) can be obtained for each r and i as the unique root of a deterministic equation.
  • A Kurushima, K Ano
    JOURNAL OF APPLIED PROBABILITY 40(4) 1147-1154 2003年12月  
    This note studies a Poisson arrival selection problem for the full-information case with an unknown intensity lambda which has a Gamma prior density G(r, 1/a), where a > 0 and r is a natural number. For the no-information case with the same setting, the problem is monotone and the one-step look-ahead rule is an optimal stopping rule; in contrast, this note proves that the full-information case is not a monotone stopping problem.
  • KURUSHIMA AIKO, Ano Katusnori
    Scientiae Mathematicae Japonicae 57(2) 217-231 2003年3月  

書籍等出版物

 1

講演・口頭発表等

 10

共同研究・競争的資金等の研究課題

 4