  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.
