Large Deviation Theory Without Probability Measures

Large deviation theory studies the asymptotic tail behaviour of sequences of probability distributions. A series of recent results have generalized the basic principles and theorems of this theory to maxitive translation invariant previsions, stripping away the probabilistic aspects of this theory. In this note we survey these results, and explain their connection to large deviation theory.