可数状态空间上马氏过程的遍历风险敏感控制
Ergodic Risk-Sensitive Control of Markov Processes on Countable State Space Revisited
摘要：
本文考虑了一类离散和连续时间控制的马氏过程，研究了遍历风险敏感极小化问题。在一个全面的稳定性假设下，我们提供了一个完整的分析。特别地，我们建立了最优平稳马尔可夫控制的值函数的唯一性和验证结果，除了存在性结果。我们也重新审视这个问题的近似单调性条件下，但没有任何稳定性假设。我们的研究结果还包括离散和连续时间框架中的政策改进算法。
英文摘要：
We consider a large family of discrete and continuous time controlled Markov processes and study an ergodic risk-sensitive minimization problem. Under a blanket stability assumption, we provide a complete analysis to this problem. In particular, we establish uniqueness of the value function and verification result for optimal stationary Markov controls, in addition to the existence results. We also revisit this problem under a near-monotonicity condition but without any stability hypothesis. Our results also include policy improvement algorithms both in discrete and continuous time frameworks.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
