We consider probabilistic automata over finite words. Such an automaton defines the language consisting of the set of words accepted with probability greater than a given threshold. We show the existence of a universally non-regular probabilistic automaton, i.e. an automaton such that the language it defines is non-regular for every threshold. As a corollary, we obtain an alternative and very s...

According to orthodox (Kolmogorovian) probability theory, conditional probabilities are by definition certain ratios of unconditional probabilities. As a result, orthodox conditional probabilities are undefined whenever their antecedents have zero unconditional probability. This has important ramifications for the notion of probabilistic independence. Traditionally, independence is defined in t...

Inductive inference in the scientific domain is seldom an individual enterprise. Many a scientific breakthrough are result of the efforts of several scientists investigating a problem; scientific success is achieved if any one or more of members of the scientific community are successful. This observation about the practice of science can be partially incorporated in a model of computational le...

We introduce the uncertain generalized probabilistic weighted averaging (UGPWA) operator. It is an aggregation operator that unifies the probability and the weighted average in the same formulation considering the degree of importance that each concept has in the aggregation. Moreover, it is able to assess uncertain environments that can not be assessed with exact numbers but it is possible to ...

In this work we develop and examine a generalized account of David Lewis’s imaging in the same way as how Jeffrey’s Probability Kinematics generalizes Bayesian conditionalization. We show that this naturally leads to a rational account of probabilistic belief removal – a rather long standing problem in the area. It turns out that our generalization of imaging indeed is an account of probabilist...

A text-independent Probabilistic Neural Network (PNN)-based speaker verification system, referred to as WCL-1, is presented. A modular structure, with a distinct PNN for each enrolled speaker, is employed. A gender-dependent universal background model is created to represent the world of possible impostor speakers. Beside portrayal of the WCL-1 system, a comprehensive description of the results...

We propose a probabilistic-logical framework for group decision-making. Its main characteristic is that we derive group preferences from agents’ beliefs and utilities rather than from their individual preferences as done in social choice approaches. This can be more appropriate when the individual preferences hide too much of the individuals’ opinions that determined their preferences. We intro...