Search Results for author:
Found 4 papers, 2 papers with code
Pontryagin Neural Operator for Solving Parametric General-Sum Differential Games
To address these challenges, we propose in this paper a Pontryagin-mode neural operator that outperforms existing state-of-the-art (SOTA) on safety performance across games with parametric state constraints.
Value Approximation for Two-Player General-Sum Differential Games with State Constraints
Solving Hamilton-Jacobi-Isaacs (HJI) PDEs numerically enables equilibrial feedback control in two-player differential games, yet faces the curse of dimensionality (CoD).
Approximating Discontinuous Nash Equilibrial Values of Two-Player General-Sum Differential Games
This paper investigates two potential solutions to this problem: a hybrid method that leverages both supervised Nash equilibria and the HJI PDE, and a value-hardening method where a sequence of HJIs are solved with a gradually hardening reward.
Lane Change Decision-Making through Deep Reinforcement Learning
Due to the complexity and volatility of the traffic environment, decision-making in autonomous driving is a significantly hard problem.
