NashOpt: A Python Library for Generalized Nash Equilibria
Research Paper#Game Theory, Optimization, Python Library🔬 Research|Analyzed: Jan 3, 2026 18:33•
Published: Dec 29, 2025 17:49
•1 min read
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This paper introduces NashOpt, a Python library designed to compute and analyze generalized Nash equilibria (GNEs) in noncooperative games. The library's focus on shared constraints and real-valued decision variables, along with its ability to handle both general nonlinear and linear-quadratic games, makes it a valuable tool for researchers and practitioners in game theory and related fields. The use of JAX for automatic differentiation and the reformulation of linear-quadratic GNEs as mixed-integer linear programs highlight the library's efficiency and versatility. The inclusion of inverse-game and Stackelberg game-design problem support further expands its applicability. The availability of the library on GitHub promotes open-source collaboration and accessibility.
Key Takeaways
- •NashOpt is a Python library for computing Generalized Nash Equilibria (GNEs).
- •It handles both nonlinear and linear-quadratic games.
- •It uses JAX for automatic differentiation.
- •It supports inverse-game and Stackelberg game-design problems.
- •The library is open-source and available on GitHub.
Reference / Citation
View Original"NashOpt is an open-source Python library for computing and designing generalized Nash equilibria (GNEs) in noncooperative games with shared constraints and real-valued decision variables."