Abstract
We study the learning problem of systolic languages from queries and counterexamples. A systolic language is specified by a systolic automaton which is a kind of network consisting of uniformly connected processors(finite automata).
In this article, we show that the class of binary systolic tree languages is learnable in polynomial time from the learning protocol what is called minimally adequate teacher.
Since the class of binary systolic tree languages properly contains the class of regular languages, the main result in this paper gives a generalization of the corresponding Angluin's result for regular languages.
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D. Angluin. Learning k-bounded context-free grammars. Res. Rep. 557, Dept. of Comput. Sci., YALE Univ, 1987.
D. Angluin. Learning regular sets from queries and counterexamples. Information and Computation, 75:87–106, 1987.
P. Berman and R. Roos. Learning one-counter languages in polynomial time. In 28th IEEE Symp. on FOCS, pages 61–67, 1987.
M. A. Harrison. Introduction to Formal Language Theory. Addison-Wesley, Reading, MA, 1978.
H.T.Kung, R.F.Sproull, and G.L.Steel Jr.(eds.). VLSI Systems and Computations. Computer Science Press, 1981.
K. Culik II, J. Gruska, and A. Salomaa. Systolic automata for VLSI on balanced trees. Acta Informatica, 18:335–344, 1983.
K. Culik II, A. Salomaa, and D. Wood. Systolic tree acceptors. R.A.I.R.O. Theoretical Informatics, 18:53–69, 1984.
H. Ishizaka. Polynomial time learnability of simple deterministic languages. Machine Learning, 5:151–164, 1990.
T. Nishino. Mathematical analysis of lexical-functional grammars—complexity, parsability, and learnability. In Proceedings of Seoul International Conference on Natural Language Processing, 1990.
Y. Sakakibara. Learning context-free grammars from structural data in polynomial time. Theoretical Computer Science, 76:223–242, 1990.
Y. Sakakibara. On learning smullyan's elementary formal systems: Towards an efficient learning for context-sensitive languages. Advances in Software Science and Technology, 2:79–101, 1990.
A. Salomaa. Formal Languages. Academic Press, New York, NY, 1973.
E. Shapiro. Inductive inference of theories from facts. Res. Rep. 192, Dept. of Comput. Sci., YALE Univ, 1981.
H. Shirakawa and T. Yokomori. Polynomial-time MAT learning of c-deterministic context-free grammars. Res. Rep. 92-04, Dept. of Comput. and Inform. Math., Univ. of Electro-Communications, 1992.
Y. Takada. Grammatical inference for even linear languages based on control sets. Information Proccesing Letters, 28:193–199, 1988.
T. Yokomori. Learning non-determinisitc finite automata from queries and counterexamples. (to appear) In Proceedings of International Workshop on Machine Intelligence '92, Glasgow, August, 1992.
T. Yokomori. On learning systolic languages. Res. Rep. 92-07, Dept. of Comput. and Inform. Math., Univ. of Electro-Communications, 1992.
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© 1993 Springer-Verlag Berlin Heidelberg
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Yokomori, T. (1993). On learning systolic languages. In: Doshita, S., Furukawa, K., Jantke, K.P., Nishida, T. (eds) Algorithmic Learning Theory. ALT 1992. Lecture Notes in Computer Science, vol 743. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-57369-0_26
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DOI: https://doi.org/10.1007/3-540-57369-0_26
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