activity
20182023
most citedMonte Carlo Continual Resolving for Online Strategy Computation in Imperfect Information Games

5 citations · 10 across the 5 of their papers we have counts for

collaborators

5 papers

cs.GT2023

Learning not to Regret

David Sychrovský, Michal Šustr, Elnaz Davoodi +3

The literature on game-theoretic equilibrium finding predominantly focuses on single games or their repeated play. Nevertheless, numerous real-world scenarios feature playing a gam…

cs.GT2021

Revisiting Game Representations: The Hidden Costs of Efficiency in Sequential Decision-making Algorithms

Vojtěch Kovařík, David Milec, Michal Šustr +2

Recent advancements in algorithms for sequential decision-making under imperfect information have shown remarkable success in large games such as limit- and no-limit poker. These a…

cs.GT2020★ 2 cited

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…

cs.GT2018★ 5 cited

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…

cs.AI2018★ 3 cited

Multi-platform Version of StarCraft: Brood War in a Docker Container: Technical Report

Michal Šustr, Jan Malý, Michal Čertický

We present a dockerized version of a real-time strategy game StarCraft: Brood War, commonly used as a domain for AI research, with a pre-installed collection of AI developement too…