Local Nash Equilibrium

Local Nash equilibrium (LNE) is a solution concept in game theory where each player's strategy is optimal given the strategies of other players, representing a stable state in multi-agent systems. Current research focuses on developing efficient algorithms, such as Newton-based methods and second-order algorithms, to find LNEs, particularly in complex settings with constraints and non-concave utilities, often employing neural networks for approximation. This work is significant for its applications in diverse fields including multi-agent reinforcement learning, trajectory prediction, and economic modeling, offering improved solutions for problems involving strategic interactions and uncertainty.