812 citations · 836 across the 4 of their papers we have counts for
6 papers
Student of Games: A unified learning algorithm for both perfect and imperfect information games
Martin Schmid, Matej Moravcik, Neil Burch +10
Games have a long history as benchmarks for progress in artificial intelligence. Approaches using search and learning produced strong performance across many perfect information ga…
Sound Algorithms in Imperfect Information Games
Michal Šustr, Martin Schmid, Matej Moravčík +3
Search has played a fundamental role in computer game research since the very beginning. And while online search has been commonly used in perfect information games such as Chess a…
Revisiting CFR+ and Alternating Updates
Neil Burch, Matej Moravcik, Martin Schmid
The CFR+ algorithm for solving imperfect information games is a variant of the popular CFR algorithm, with faster empirical performance on a range of problems. It was introduced wi…
Variance Reduction in Monte Carlo Counterfactual Regret Minimization (VR-MCCFR) for Extensive Form Games using Baselines
Martin Schmid, Neil Burch, Marc Lanctot +3
Learning strategies for imperfect information games from samples of interaction is a challenging problem. A common method for this setting, Monte Carlo Counterfactual Regret Minimi…
DeepStack: Expert-Level Artificial Intelligence in No-Limit Poker
Matej Moravčík, Martin Schmid, Neil Burch +7
Artificial intelligence has seen several breakthroughs in recent years, with games often serving as milestones. A common feature of these games is that players have perfect informa…
AIVAT: A New Variance Reduction Technique for Agent Evaluation in Imperfect Information Games
Neil Burch, Martin Schmid, Matej Moravčík +1
Evaluating agent performance when outcomes are stochastic and agents use randomized strategies can be challenging when there is limited data available. The variance of sampled outc…