After an apparent hiatus of roughly 30 years, we revisit a seemingly neglected subject in the theory of (one-dimensional) cellular automata: sublinear-time computation. The model considered is that of ACAs, which are language acceptors whose acceptance condition depends on the states of all cells in the automaton. We prove a time hierarchy theorem for sublinear-time ACA classes, analyze their intersection with the regular languages, and, finally, establish strict inclusions in the parallel computation classes SC and (uniform) AC. As an addendum, we introduce and investigate the concept of a decider ACA (DACA) as a candidate for a decider counterpart to (acceptor) ACAs. We show the class of languages decidable in constant time by DACAs equals the locally testable languages, and we also determine Ω(√n) as the (tight) time complexity threshold for DACAs up to which no advantage compared to constant time is possible.
CITATION STYLE
Modanese, A. (2020). Sublinear-Time Language Recognition and Decision by One-Dimensional Cellular Automata. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12086 LNCS, pp. 251–265). Springer. https://doi.org/10.1007/978-3-030-48516-0_19
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