Statistical inductive learning of regular formal languages

Author(s):  
Juan Andrés Sánchez ◽  
José Miguel Benedí
2011 ◽  
Author(s):  
Monica S. Birnbaum ◽  
Robert A. Bjork ◽  
Elizabeth Ligon Bjork
Keyword(s):  

2017 ◽  
Vol 23 (4) ◽  
pp. 403-416 ◽  
Author(s):  
Veronica X. Yan ◽  
Nicholas C. Soderstrom ◽  
Gayan S. Seneviratna ◽  
Elizabeth Ligon Bjork ◽  
Robert A. Bjork

2021 ◽  
Vol 180 (1-2) ◽  
pp. 151-177
Author(s):  
Qichao Wang

Weighted restarting automata have been introduced to study quantitative aspects of computations of restarting automata. In earlier works we studied the classes of functions and relations that are computed by weighted restarting automata. Here we use them to define classes of formal languages by restricting the weight associated to a given input word through an additional requirement. In this way, weighted restarting automata can be used as language acceptors. First, we show that by using the notion of acceptance relative to the tropical semiring, we can avoid the use of auxiliary symbols. Furthermore, a certain type of word-weighted restarting automata turns out to be equivalent to non-forgetting restarting automata, and another class of languages accepted by word-weighted restarting automata is shown to be closed under the operation of intersection. This is the first result that shows that a class of languages defined in terms of a quite general class of restarting automata is closed under intersection. Finally, we prove that the restarting automata that are allowed to use auxiliary symbols in a rewrite step, and to keep on reading after performing a rewrite step can be simulated by regular-weighted restarting automata that cannot do this.


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