812 citations · 819 across the 12 of their papers we have counts for
7 papers · 1 filter
Equilibrium Refinements Improve Subgame Solving in Imperfect-Information Games
Ondrej Kubicek, Viliam Lisy, Tuomas Sandholm
Subgame solving is a technique for scaling algorithms to large games by locally refining a precomputed blueprint strategy during gameplay. While straightforward in perfect-informat…
Understanding Optimal Portfolios of Strategies for Solving Two-player Zero-sum Games
Karolina Drabent, Ondřej Kubíček, Viliam Lisý
In large-scale games, approximating the opponent's strategy space with a small portfolio of representative strategies is a common and powerful technique. However, the construction…
Look-ahead Search on Top of Policy Networks in Imperfect Information Games
Ondrej Kubicek, Neil Burch, Viliam Lisy
Search in test time is often used to improve the performance of reinforcement learning algorithms. Performing theoretically sound search in fully adversarial two-player games with…
Problems with the EFG formalism: a solution attempt using observations
Vojtěch Kovařík, Viliam Lisý
We argue that the extensive-form game (EFG) model isn't powerful enough to express all important aspects of imperfect information games, such as those related to decomposition and…
Monte Carlo Continual Resolving for Online Strategy Computation in Imperfect Information Games
Michal Sustr, Vojtech Kovarik, Viliam Lisy
Online game playing algorithms produce high-quality strategies with a fraction of memory and computation required by their offline alternatives. Continual Resolving (CR) is a recen…
Analysis of Hannan Consistent Selection for Monte Carlo Tree Search in Simultaneous Move Games
Vojtěch Kovařík, Viliam Lisý
Hannan consistency, or no external regret, is a~key concept for learning in games. An action selection algorithm is Hannan consistent (HC) if its performance is eventually as good…