共 2 条
MAXIMIZING THE PROBABILITY OF VISITING A SET INFINITELY OFTEN FOR A MARKOV DECISION PROCESS WITH BOREL STATE AND ACTION SPACES
被引:0
|作者:
Dufour, Francois
[1
]
Prieto-Rumeau, Tomas
[2
]
机构:
[1] INRIA Team Astral, 200 Ave Vieille Tour, F-33405 Talence, France
[2] UNED, Fac Sci, Dept Stat Operat Res & Numer Calculus, calle Juan del Rosal 10, Madrid 28040, Spain
关键词:
Markov decision process;
visiting a set infinitely often;
non-additive optimality criterion;
Young measures;
ws(infinity)-topology;
TOTAL-COST CRITERION;
POLICIES;
COMPACTNESS;
D O I:
10.1017/jpr.2024.25
中图分类号:
O21 [概率论与数理统计];
C8 [统计学];
学科分类号:
020208 ;
070103 ;
0714 ;
摘要:
We consider a Markov control model with Borel state space, metric compact action space, and transitions assumed to have a density function with respect to some probability measure satisfying some continuity conditions. We study the optimization problem of maximizing the probability of visiting some subset of the state space infinitely often, and we show that there exists an optimal stationary Markov policy for this problem. We endow the set of stationary Markov policies and the family of strategic probability measures with adequate topologies (namely, the narrow topology for Young measures and the ws(infinity)-topology, respectively) to obtain compactness and continuity properties, which allow us to obtain our main results.
引用
收藏
页码:1424 / 1447
页数:24
相关论文