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ICML
2003
IEEE
16 years 7 months ago
AWESOME: A General Multiagent Learning Algorithm that Converges in Self-Play and Learns a Best Response Against Stationary Oppon
A satisfactory multiagent learning algorithm should, at a minimum, learn to play optimally against stationary opponents and converge to a Nash equilibrium in self-play. The algori...
Vincent Conitzer, Tuomas Sandholm
ISIPTA
2003
IEEE
125views Mathematics» more  ISIPTA 2003»
16 years 22 hour ago
Game-Theoretic Learning Using the Imprecise Dirichlet Model
We discuss two approaches for choosing a strategy in a two-player game. We suppose that the game is played a large number of rounds, which allows the players to use observations o...
Erik Quaeghebeur, Gert de Cooman
CA
2003
IEEE
16 years 1 days ago
Satisfying the Perceived Need for Free-Play in Pedagogically Oriented Interactive Dramas
This research explores ways of harnessing people’s passion for entertainment in order to stimulate players to attain the meta-learning skills they need for lifelong learning and...
Barry G. Silverman, Michael Johns, Ransom Weaver
FPLAY
2008
15 years 8 months ago
Interactive accounting simulation environment for accounting education and training
In contrast to traditional teaching-and-learning environments whereby the teacher controls the learning (e.g., teacher-centered), video games present a learner-centered approach t...
Andrew Milner, Andrew Hogue, Bill Kapralos, John F...
RSKT
2009
Springer
16 years 1 months ago
Learning Optimal Parameters in Decision-Theoretic Rough Sets
A game-theoretic approach for learning optimal parameter values for probabilistic rough set regions is presented. The parameters can be used to define approximation regions in a p...
Joseph P. Herbert, Jingtao Yao