On Learning Polynomial Recursive Programs

Alex Buna-Marginean, Vincent Cheval,Mahsa Shirmohammadi,James Worrell

CoRR(2023)

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摘要
We introduce the class of P-finite automata. These are a generalisation of weighted automata, in which the weights of transitions can depend polynomially on the length of the input word. P-finite automata can also be viewed as simple tail-recursive programs in which the arguments of recursive calls can non-linearly refer to a variable that counts the number of recursive calls. The nomenclature is motivated by the fact that over a unary alphabet P-finite automata compute so-called P-finite sequences, that is, sequences that satisfy a linear recurrence with polynomial coefficients. Our main result shows that P-finite automata can be learned in polynomial time in Angluin's MAT exact learning model. This generalises the classical results that deterministic finite automata and weighted automata over a field are respectively polynomial-time learnable in the MAT model.
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关键词
Automata learning,Exact learning,Holonomic sequences,P-finite sequences,Weighted automata
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