Λεπτομέρειες βιβλιογραφικής εγγραφής
| Τίτλος: |
Monotone Near-Zero-Sum Games: A Generalization of Convex-Concave Minimax |
| Συγγραφείς: |
Luo, Ruichen, Stich, Sebastian U., Chatterjee, Krishnendu |
| Έτος έκδοσης: |
2025 |
| Θεματικοί όροι: |
Computer Science and Game Theory, Optimization and Control |
| Περιγραφή: |
Zero-sum and non-zero-sum (aka general-sum) games are relevant in a wide range of applications. While general non-zero-sum games are computationally hard, researchers focus on the special class of monotone games for gradient-based algorithms. However, there is a substantial gap between the gradient complexity of monotone zero-sum and monotone general-sum games. Moreover, in many practical scenarios of games the zero-sum assumption needs to be relaxed. To address these issues, we define a new intermediate class of monotone near-zero-sum games that contains monotone zero-sum games as a special case. Then, we present a novel algorithm that transforms the near-zero-sum games into a sequence of zero-sum subproblems, improving the gradient-based complexity for the class. Finally, we demonstrate the applicability of this new class to model practical scenarios of games motivated from the literature. |
| Τύπος εγγράφου: |
Working Paper |
| DOI: |
10.48550/arXiv.2512.02690 |
| Σύνδεσμος πρόσβασης: |
http://arxiv.org/abs/2512.02690 |
| Αριθμός Καταχώρησης: |
edsarx.2512.02690 |
| Βάση Δεδομένων: |
arXiv |