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1942. An enhanced gradient algorithm for computing generalized Nash equilibrium
Invited abstract in session TC-36: Game Theory, Solutions and Structures VII, stream Game Theory, Solutions and Structures.
Tuesday, 12:30-14:00Room: 32 (building: 306)
Authors (first author is the speaker)
| 1. | Fellipe Santos
|
| PC/AR, CEMIG | |
| 2. | Adriano Lisboa
|
| Gaia, solutions on demand | |
| 3. | Douglas Vieira
|
| ENACOM | |
| 4. | Rodney Saldanha
|
| Departamento de Engenharia Elétrica, Universidade Federal de Minas Gerias |
Abstract
This paper introduces an enhanced algorithm for computing generalized Nash equilibria in multiple-player nonlinear games. The algorithm degenerates into a gradient algorithm for single-player games (i.e., optimization problems) or potential games (i.e., equivalent to minimizing the respective potential function), similar to the Rosen gradient algorithm. Analytical examples demonstrate that it has similar theoretical guarantees of finding a generalized Nash equilibrium when compared to the relaxation algorithm, while numerical examples show that it is faster. Furthermore, the proposed algorithm is as fast as, but more stable than, the Rosen gradient algorithm, especially when dealing with constraints and non-convex games. The proposed strategy is tested in benchmarking game theory problems and real-world applications.
Keywords
- Game Theory
- Decision Support Systems
- Electricity Markets
Status: accepted
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