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
2x2 matrix games, they behave quite differently.Comment: 16 LaTeX pages, 8 eps figure

Hutter, Marcus

Poland, Jan

English

arXiv

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 learning algorithms are not even informed
                  about the game they are playing

Universal Learning of Repeated Matrix Games

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