Abstract
The size of deterministic automata required for recognizing regular and ω-regular languages is a well-studied measure for the complexity of languages. We introduce and study a new complexity measure, based on the sensing required for recognizing the language. Intuitively, the sensing cost quantifies the detail in which a random input word has to be read in order to decide its membership in the language. We study the sensing cost of regular and ω-regular languages, as well as applications of the study in practice, especially in the monitoring and synthesis of reactive systems.
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CITATION STYLE
Almagor, S., Kuperberg, D., & Kupferman, O. (2017). Sensing as a complexity measure. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10316 LNCS, pp. 3–15). Springer Verlag. https://doi.org/10.1007/978-3-319-60252-3_1
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