Data‐Driven Stochastic Game Theoretic Differential Dynamic Programming

ABSTRACT This paper introduces a novel approach for designing optimal control using data‐driven Stochastic Game Theoretic Differential Dynamic Programming (SGT‐DDP). The proposed method addresses unknown stochastic systems by approximating both drift and diffusion dynamics. The drift dynamics is est...

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Veröffentlicht in:	International journal of robust and nonlinear control Jg. 35; H. 13; S. 5343 - 5354
Hauptverfasser:	Sarbaz, Mohammad, Sun, Wei
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Hoboken, USA John Wiley & Sons, Inc 10.09.2025 Wiley Subscription Services, Inc
Schlagworte:	Approximation differential dynamic programming Drift estimation Dynamic programming Dynamical systems Game theory Gaussian process gaussian process regression Nonlinear systems Optimal control stochastic dynamics Stochastic systems
ISSN:	1049-8923, 1099-1239
Online-Zugang:	Volltext
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