11 citations · 14 across the 3 of their papers we have counts for
6 papers · 1 filter
AI Testing Should Account for Sophisticated Strategic Behaviour
Vojtech Kovarik, Eric Olav Chen, Sami Petersen +2
This position paper argues for two claims regarding AI testing and evaluation. First, to remain informative about deployment behaviour, evaluations need account for the possibility…
Adapting Beyond the Depth Limit: Counter Strategies in Large Imperfect Information Games
David Milec, Vojtěch Kovařík, Viliam Lisý
We study the problem of adapting to a known sub-rational opponent during online play while remaining robust to rational opponents. We focus on large imperfect-information (zero-sum…
Game Theory with Simulation in the Presence of Unpredictable Randomisation
Vojtech Kovarik, Nathaniel Sauerberg, Lewis Hammond +1
AI agents will be predictable in certain ways that traditional agents are not. Where and how can we leverage this predictability in order to improve social welfare? We study this q…
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…