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Output feedback Q-learning for discrete-time finite-horizon zero-sum games with application to the <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si7.svg"><mml:mrow><mml:msub><mml:mrow><mml:mi>H</mml:mi></mml:mrow><mml:mrow><mml:mi>∞</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math> control

Mingxiang Liu, Qianqian Cai, Dandan Li, Wei Meng, Minyue Fu

2023Neurocomputing15 citationsDOI

Topics & Concepts

Context (archaeology)HorizonState (computer science)Function (biology)Zero-sum gameZero (linguistics)Computer scienceOptimal controlApplied mathematicsMathematicsAlgorithmMathematical optimizationNash equilibriumPaleontologyGeometryEvolutionary biologyBiologyPhilosophyLinguisticsAdaptive Dynamic Programming ControlAdvanced Control Systems OptimizationFrequency Control in Power Systems
Output feedback Q-learning for discrete-time finite-horizon zero-sum games with application to the <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si7.svg"><mml:mrow><mml:msub><mml:mrow><mml:mi>H</mml:mi></mml:mrow><mml:mrow><mml:mi>∞</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math> control | Litcius