  Works, briefly surveyed here, are concerned with two basic methods: Maximum
Probability and Bayesian Maximum Probability; as well as with their asymptotic
instances: Relative Entropy Maximization and Maximum Non-parametric Likelihood.
Parametric and empirical extensions of the latter methods - Empirical Maximum
Maximum Entropy and Empirical Likelihood - are also mentioned. The methods are
viewed as tools for solving certain ill-posed inverse problems, called
Pi-problem, Phi-problem, respectively. Within the two classes of problems,
probabilistic justification and interpretation of the respective methods are
discussed.
