Reachability Analysis in Stochastic Directed Graphs by Reinforcement Learning-Reference-Cited by-同舟云学术

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Reachability Analysis in Stochastic Directed Graphs by Reinforcement Learning

Published:2023-01 Issue:1 Volume:68 Page:462-469
ISSN:0018-9286
Container-title:IEEE Transactions on Automatic Control
language:
Short-container-title:IEEE Trans. Automat. Contr.

Author:

Possieri Corrado¹^ORCID,Frasca Mattia²^ORCID,Rizzo Alessandro³^ORCID

Affiliation:

1. Istituto di Analisi dei Sistemi ed Informatica “A. Ruberti”, Consiglio Nazionale delle Ricerche (IASI-CNR), Roma, Italy

2. Dipartimento di Ingegneria Elettrica Elettronica e Informatica, University of Catania, Catania, Italy

3. Dipartimento di Elettronica e Telecomunicazioni, Politecnico di Torino, Torino, Italy

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/9/10002258/09681282.pdf?arnumber=9681282

Reference18 articles.

1. A Lyapunov theorem certifying global weak reachability for stochastic difference inclusions with random inputs

2. A Converse Lyapunov Theorem and Robustness for Asymptotic Stability in Probability

3. Markov Chains

4. Discrete-time stochastic control systems: Examples of robustness to strictly causal perturbations

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Reinforcement Learning for Non-Deterministic Transition Systems With an Application to Symbolic Control;IEEE Control Systems Letters;2023

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