A data-driven α-policy iteration algorithm for optimal leader-following consensus of discrete-time multi-agent systems

In this paper, the data-driven α-policy iteration (PI) algorithm is proposed to address the optimal leader-following consensus problem of discrete-time multi-agent systems (MASs). Unlike existing results for state consensus problem that utilise the PI algorithm, the novel algorithm leverages only th...

Celý popis

Podrobná bibliografia

Vydané v:	International journal of systems science Ročník 56; číslo 16; s. 4055 - 4072
Hlavní autori:	Xiang, Aoxue, Zhao, Xinyuan, Ma, Ruicheng
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	London Taylor & Francis 10.12.2025 Taylor & Francis Ltd
Predmet:	Bellman theory Discrete time systems Iterative algorithms Linear quadratic regulator model-free Multi-agent systems Multiagent systems reinforcement learning state consensus α-policy iteration
ISSN:	0020-7721, 1464-5319
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!