Zobrazeno 1 - 10
of 165
pro vyhledávání: '"Moravčik, P"'
Autor:
Moravcik, Igor, Alfreider, Markus, Wurster, Stefan, Schretter, Lukas, Zadera, Antonin, Pernica, Vítezslav, Čamek, Libor, Eckert, Jürgen, Hohenwarter, Anton
The mechanical performance and microstructures of a CoCrNi medium-entropy alloy (MEA) and NCoCrNi, alloyed with 0.5at% N, after high pressure torsion (HPT) and subsequent annealing treatments in a temperature range of 150-1000 {\deg}C were investigat
Externí odkaz:
http://arxiv.org/abs/2408.03606
Autor:
Schmid, Martin, Moravcik, Matej, Burch, Neil, Kadlec, Rudolf, Davidson, Josh, Waugh, Kevin, Bard, Nolan, Timbers, Finbarr, Lanctot, Marc, Holland, G. Zacharias, Davoodi, Elnaz, Christianson, Alden, Bowling, Michael
Publikováno v:
Science Advances 9, eadg3256 (2023)
Games have a long history as benchmarks for progress in artificial intelligence. Approaches using search and learning produced strong performance across many perfect information games, and approaches using game-theoretic reasoning and learning demons
Externí odkaz:
http://arxiv.org/abs/2112.03178
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 and Go, online search methods for imperfect information games have only
Externí odkaz:
http://arxiv.org/abs/2006.08740
Akademický článek
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Publikováno v:
Journal of Artificial Intelligence Research 64 (2019) 429-443
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 with a theoretical upper bound on solution error, but subsequent work sh
Externí odkaz:
http://arxiv.org/abs/1810.11542
Autor:
Schmid, Martin, Burch, Neil, Lanctot, Marc, Moravcik, Matej, Kadlec, Rudolf, Bowling, Michael
Learning strategies for imperfect information games from samples of interaction is a challenging problem. A common method for this setting, Monte Carlo Counterfactual Regret Minimization (MCCFR), can have slow long-term convergence rates due to high
Externí odkaz:
http://arxiv.org/abs/1809.03057
Autor:
Moravčík, Matej, Schmid, Martin, Burch, Neil, Lisý, Viliam, Morrill, Dustin, Bard, Nolan, Davis, Trevor, Waugh, Kevin, Johanson, Michael, Bowling, Michael
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 information. Poker is the quintessential game of imperfect information, and a
Externí odkaz:
http://arxiv.org/abs/1701.01724
Akademický článek
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Akademický článek
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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 outcomes may make the simple approach of Monte Carlo sampling inadequate.
Externí odkaz:
http://arxiv.org/abs/1612.06915