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Introduction to Automata Theory, Languages, and Computation
TLDR
This book is a rigorous exposition of formal languages and models of computation, with an introduction to computational complexity, appropriate for upper-level computer science undergraduates who are comfortable with mathematical arguments.Abstract:
This book is a rigorous exposition of formal languages and models of computation, with an introduction to computational complexity. The authors present the theory in a concise and straightforward manner, with an eye out for the practical applications. Exercises at the end of each chapter, including some that have been solved, help readers confirm and enhance their understanding of the material. This book is appropriate for upper-level computer science undergraduates who are comfortable with mathematical arguments.read more
Citations
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Journal ArticleDOI
Formal verification of autonomous vehicle platooning
TL;DR: A mixed strategy of formal verification and global verification allows us to verify safety requirements not only of a model of the system, but of the actual agent code used to program the autonomous vehicles.
Book ChapterDOI
The complexity of sparse sets in P
TL;DR: The complexity of sparse sets in P is shown to be central to certain questions about circuit complexity classes and about one-way functions.
Journal ArticleDOI
A multiparameter analysis of the boundedness problem for vector addition systems
Louis E. Rosier,Hsu-Chun Yen +1 more
TL;DR: It is shown that the Boundedness Problem (BP), for VASS(k, l, n), can be solved in O((l + log n)∗2c∗k∗logk) nondeterministic space, and that the BP is PSPACE-complete for four-dimensional VASSs, and NP-hard for two-dimensionalVASSs.
Book ChapterDOI
Universal Algorithmic Intelligence: A Mathematical Top→Down Approach
Marcus Hutter,Marcus Hutter +1 more
TL;DR: In this paper, a parameter-free theory of universal artificial intelligence is proposed and the AIXI model is shown to be the most intelligent unbiased agent possible in a number of problem classes, including sequence prediction, strategic games, function minimization, reinforcement and supervised learning.
Book ChapterDOI
Markov Source Modeling of Text Generation
TL;DR: A language model is a conceptual device which, given a string of past words, provides an estimate of the probability that any given word from an allowed vocabulary will follow the string.
References
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Book ChapterDOI
Representation of Events in Nerve Nets and Finite Automata
TL;DR: This memorandum is devoted to an elementary exposition of the problems and of results obtained on the McCulloch-Pitts nerve net during investigations in August 1951.