Cargando…
Learn Quasi-Stationary Distributions of Finite State Markov Chain
We propose a reinforcement learning (RL) approach to compute the expression of quasi-stationary distribution. Based on the fixed-point formulation of quasi-stationary distribution, we minimize the KL-divergence of two Markovian path distributions induced by candidate distribution and true target dis...
Autores principales: | Cai, Zhiqiang, Lin, Ling, Zhou, Xiang |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8774945/ https://www.ncbi.nlm.nih.gov/pubmed/35052159 http://dx.doi.org/10.3390/e24010133 |
Ejemplares similares
-
Quasi-Stationary Distributions: Markov Chains, Diffusions and Dynamical Systems
por: Collet, Pierre, et al.
Publicado: (2013) -
Markov chains with stationary transition probabilities
por: Chung, Kai Lai
Publicado: (1960) -
Markov chains: with stationary transition probabilities
por: Chung, Kai Lai
Publicado: (1967) -
Self-learning control of finite Markov chains /
por: Poznyak, Alexander S.
Publicado: (2000) -
A methodology for stochastic analysis of share prices as Markov chains with finite states
por: Mettle, Felix Okoe, et al.
Publicado: (2014)