3 papers
cs.GT2025
Perturbing Best Responses in Zero-Sum Games
Adam Dziwoki, Rostislav Horcik
This paper investigates the impact of perturbations on the best-response-based algorithms approximating Nash equilibria in zero-sum games, namely Double Oracle and Fictitious Play.…
cs.AI2024
Deep Learning for Generalised Planning with Background Knowledge
Dillon Z. Chen, Rostislav Horčík, Gustav Šír
Automated planning is a form of declarative problem solving which has recently drawn attention from the machine learning (ML) community. ML has been applied to planning either as a…
cs.GT2020
Double Oracle Algorithm for Computing Equilibria in Continuous Games
Lukáš Adam, Rostislav Horčík, Tomáš Kasl +1
Many efficient algorithms have been designed to recover Nash equilibria of various classes of finite games. Special classes of continuous games with infinite strategy spaces, such…