Universal learning of repeated matrix games
We study and compare the learning dynamics of two universal learning algorithms, one based on Bayesian learning and the other on prediction with expert advice. Both approaches have strong asymptotic performance guarantees. When confronted with the task of finding good long-term strategies in repeated 2 x 2 matrix games, they behave quite differently. We consider the case where the...[Show more]
|Collections||ANU Research Publications|
|Book Title:||Proceedings of the 15th Annual Machine Learning Conference of Belgium and The Netherlands Benelearn'06|
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