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AAAI
2010
9 years 4 months ago
Understanding the Success of Perfect Information Monte Carlo Sampling in Game Tree Search
Perfect Information Monte Carlo (PIMC) search is a practical technique for playing imperfect information games that are too large to be optimally solved. Although PIMC search has ...
Jeffrey Richard Long, Nathan R. Sturtevant, Michae...
ACG
2009
Springer
9 years 9 months ago
Monte-Carlo Tree Search in Settlers of Catan
Abstract. Games are considered important benchmark tasks of artificial intelligence research. Modern strategic board games can typically be played by three or more people, which m...
Istvan Szita, Guillaume Chaslot, Pieter Spronck
ATAL
2015
Springer
3 years 10 months ago
Online Monte Carlo Counterfactual Regret Minimization for Search in Imperfect Information Games
Online search in games has been a core interest of artificial intelligence. Search in imperfect information games (e.g., Poker, Bridge, Skat) is particularly challenging due to t...
Viliam Lisý, Marc Lanctot, Michael H. Bowli...
CG
2006
Springer
9 years 6 months ago
A Skat Player Based on Monte-Carlo Simulation
We apply Monte Carlo simulation and alpha-beta search to the card game of Skat, which is similar to Bridge, but different enough to require some new algorithmic ideas besides the t...
Sebastian Kupferschmid, Malte Helmert
AE
2015
Springer
3 years 10 months ago
Towards Human-Competitive Game Playing for Complex Board Games with Genetic Programming
Recent works have shown that Genetic Programming (GP) can be quite successful at evolving human-competitive strategies for games ranging from classic board games, such as chess, to...
Denis Robilliard, Cyril Fonlupt
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