We present a powerful quasi-probabilistic default formalism for graded defaults based on a well-motivated canonical ranking construction procedure, System JLZ. It implements the minimal construction paradigm and verifies the major inference principles and inheritance desiderata, including rational monotony for propositions and structured cumulativity for default conditionals. With help from a s...

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 viewe...

It has been proposed that the general function of the brain is inference, which corresponds quantitatively to the minimization of uncertainty (or the maximization of information). However, there has been a lack of clarity about exactly what this means. Efforts to quantify information have been in agreement that it depends on probabilities (through Shannon entropy), but there has long been a dis...

The subject of this work is the parametric inference problem, i.e. how to infer from data on the parameters of the data likelihood of a random process whose parametric form is known a priori. The assumption that Bayes’ theorem has to be used to add new data samples reduces the problem to the question of how to specify a prior before having seen any data. For this subproblem three theorems are s...

Thermodynamic modeling of extensive systems usually implicitly assumes the additivity of entropy. Furthermore, if this modeling is based on the concept of Shannon entropy, additivity of the latter function must also be guaranteed. In this case, the constituents of a thermodynamic system are treated as subsystems of a compound system, and the Shannon entropy of the compound system must be subjec...

Even though power-law or close-to-power-law degree distributions are ubiquitously observed in a great variety of large real networks, the mathematically satisfactory treatment of random power-law graphs satisfying basic statistical requirements of realism is still lacking. These requirements are: sparsity, exchangeability, projectivity, and unbiasedness. The last requirement states that entropy...

The maximum entropy principle (MEP), which has been popular in the modeling of droplet size and velocity distribution in sprays, is, strictly speaking, only applicable for isolated systems in thermodynamic equilibrium; whereas the spray formation processes are irreversible and non-isolated with interaction between the atomizing liquid and its surrounding gas medium. In this study, a new model f...