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ATAL
2008
Springer
8 years 5 months ago
On the usefulness of opponent modeling: the Kuhn Poker case study
The application of reinforcement learning algorithms to Partially Observable Stochastic Games (POSG) is challenging since each agent does not have access to the whole state inform...
Alessandro Lazaric, Mario Quaresimale, Marcello Re...
AUSAI
2001
Springer
8 years 7 months ago
An Investigation of an Adaptive Poker Player
: Other work has shown that adaptive learning can be highly successful in developing programs which are able to play games at a level similar to human players and, in some cases, e...
Graham Kendall, Mark Willdig
ATAL
2015
Springer
2 years 11 months ago
Decision-theoretic Clustering of Strategies
Clustering agents by their behaviour can be crucial for building effective agent models. Traditional clustering typically aims to group entities together based on a distance metr...
Nolan Bard, Deon Nicholas, Csaba Szepesvári...
ML
2006
ACM
8 years 3 months ago
Universal parameter optimisation in games based on SPSA
Most game programs have a large number of parameters that are crucial for their performance. While tuning these parameters by hand is rather difficult, efficient and easy to use ge...
Levente Kocsis, Csaba Szepesvári
ATAL
2010
Springer
8 years 4 months ago
Planning against fictitious players in repeated normal form games
Planning how to interact against bounded memory and unbounded memory learning opponents needs different treatment. Thus far, however, work in this area has shown how to design pla...
Enrique Munoz de Cote, Nicholas R. Jennings
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