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Yong-Zhao Hua

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Open access Oct 2026

Online distributed NE seeking for multi-agent noncooperative games with time-varying delays

A distributed online gradient-descent algorithm is developed to seek the time-varying Nash equilibrium in the game and is proven to achieve a sublinear dynamic regret bound via an appropriate learning rate, provided that the path variations grow sublinearly.

Ling-Fei Su, Yong-Zhao Hua, Xi-Wang Dong et al. · 0 citations
Oct 2026

MaTF: Maneuver-Aware Temporal Fusion for Trajectory Prediction Under Arbitrary Observation Length

Trajectory prediction is essential for many robotic applications, yet most existing models rely on fixed-length observations and struggle with temporally irregular inputs. In real-world settings, prediction difficulty further increases when agents exhibit strong maneuverability, as their future motions depend on distin...

Shuobo Wang, Wen-Yuan Qin, Yong-Zhao Hua et al. · 0 citations

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