812 citations · 929 across the 10 of their papers we have counts for
6 papers · 1 filter
Search in Imperfect Information Games
Martin Schmid
From the very dawn of the field, search with value functions was a fundamental concept of computer games research. Turing's chess algorithm from 1950 was able to think two moves ah…
Solving Common-Payoff Games with Approximate Policy Iteration
Samuel Sokota, Edward Lockhart, Finbarr Timbers +6
For artificially intelligent learning systems to have widespread applicability in real-world settings, it is important that they be able to operate decentrally. Unfortunately, dece…
The Advantage Regret-Matching Actor-Critic
Audrūnas Gruslys, Marc Lanctot, Rémi Munos +10
Regret minimization has played a key role in online learning, equilibrium computation in games, and reinforcement learning (RL). In this paper, we describe a general model-free RL…
Rethinking Formal Models of Partially Observable Multiagent Decision Making
Vojtěch Kovařík, Martin Schmid, Neil Burch +2
Multiagent decision-making in partially observable environments is usually modelled as either an extensive-form game (EFG) in game theory or a partially observable stochastic game…
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…