Ergodic Risk-sensitive control -- A survey
Not on the map. Why?
Abstract (arXiv)
Risk-sensitive control has received considerable interest since the seminal work of Howard and Matheson [120] because of its ability to account for fluctuations about the mean, its connection with H_∞ control, and its application to financial mathematics. In this article, we attempt to put together a comprehensive survey on the research done on ergodic risk-sensitive control over the last four decades.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 31 Dec 2022.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2025: 1; 2026: 3.
4 papers.
- 2025Planning and Learning in Average Risk-aware MDPscited by 2
- 2026Model-Agnostic Solutions for Deep Reinforcement Learning in Non-Ergodic Contextscited by 1
- 2026Reinforcement learning with an expectile-based objectivecited by 0
- 2026Finite-Time Analysis of Discounted Exponential-Utility Reinforcement Learningcited by 0
- 2026Finite-Time Analysis of Discounted Exponential-Utility Reinforcement Learning3 Aug 2026
- 2026Reinforcement learning with an expectile-based objective10 Feb 2026
- 2026Model-Agnostic Solutions for Deep Reinforcement Learning in Non-Ergodic Contexts13 Jan 2026
- 2025Planning and Learning in Average Risk-aware MDPs22 Mar 2025