Efficient learnability using the state merging algorithm is known for a subclass of probabilistic automata termed µ-distinguishable. In this paper, we prove that state merging alg...
Omri Guttman, S. V. N. Vishwanathan, Robert C. Wil...
Abstract. Probabilistic finite automata (PFA) model stochastic languages, i.e. probability distributions over strings. Inferring PFA from stochastic data is an open field of rese...
The value 1 problem is a decision problem for probabilistic automata on finite words: given a probabilistic automaton A, are there words accepted by A with probability arbitraril...
We focus on the estimation of a probability distribution over a set of trees. We consider here the class of distributions computed by weighted automata - a strict generalization of...
Cellular learning automata is a combination of learning automata and cellular automata. This model is superior to cellular learning automata because of its ability to learn and als...