We consider graph Turing machines, a model of parallel computation on a graph, which provides a natural generalization of several standard computational models, including ordinary Turing machines and cellular automata. In this extended abstract, we give bounds on the computational strength of functions that graph Turing machines can compute. We also begin the study of the relationship between the computational power of a graph Turing machine and structural properties of its underlying graph.
CITATION STYLE
Ackerman, N. L., & Freer, C. E. (2017). Graph turing machines. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10388 LNCS, pp. 1–13). Springer Verlag. https://doi.org/10.1007/978-3-662-55386-2_1
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