automata

简明释义

英[ɔːˈtɒmətə]美[ɔːˈtɑːmətə]

n. 不动脑筋机械行事的人；自动装置；小机器人（automaton的复数）

英英释义

单词用法

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例句

1.Propese a real-time workflow time modeling and verification method based on timed automata.

提出一种基于时间自动机的实时工作流时间建模与验证方法。

2.The applications of cellular automata method in materials design including recrystallization and solidification phase changes have been reviewed.

综述了元胞自动机方法在材料设计中的应用，包括再结晶方面和相变方面。

3.The feature of this approach is that automata , used for developing, are.

这种方法的特点是自动机，开发利用，是。

4.This paper proposes a condition of timed tree automata recognizing language, proves the correctness of its.

本文提出了时间树自动机识别语言的一个条件，并证明了结论的正确性。

5.Lattice-valued finite automata. We introduce the conpect of lattice-valued finite automata. The state transition function is defined as ?

格值有限状态自动机的研究：首先，提出了格值有限状态自动机的概念，它的状态转移函数定义为?。

6.Cellular Automata (ca) is an effective tool used to simulate complicated social and economical system.

元胞自动机是模拟复杂社会经济系统的有效工具。

7.In computer science, we study various types of automata 自动机, including finite state machines and pushdown automata.

在计算机科学中，我们研究各种类型的自动机 自动机，包括有限状态机和下推自动机。

8.The theory of automata 自动机 is fundamental for understanding how computers process information.

自动机自动机理论是理解计算机如何处理信息的基础。

9.Many programming languages are designed based on the principles of automata 自动机 theory.

许多编程语言是基于自动机 自动机理论的原则设计的。

10.Researchers are exploring the use of automata 自动机 in artificial intelligence applications.

研究人员正在探索在人工智能应用中使用自动机 自动机。

11.The behavior of complex systems can often be modeled using automata 自动机.

复杂系统的行为通常可以使用自动机 自动机进行建模。

作文

In the realm of computer science and mathematics, the concept of automata (自动机) plays a crucial role in understanding computation and its limits. An automaton (自动机) can be defined as a mathematical model that represents a system capable of performing a sequence of operations or transformations based on a set of predefined rules. This model serves as a foundation for various fields such as linguistics, artificial intelligence, and software engineering. The study of automata (自动机) theory is essential for grasping how machines process information and make decisions. At its core, automata (自动机) theory explores the behaviors of abstract machines, which can be classified into several types, including finite automata (有限自动机), pushdown automata (下推自动机), and Turing machines. Each type has its own unique characteristics and applications, making them suitable for different computational tasks. Finite automata (有限自动机), for instance, are used to recognize patterns within input strings. They operate using a finite number of states and transitions between those states based on input symbols. This simplicity makes finite automata (有限自动机) particularly useful in designing lexical analyzers for programming languages, where they help identify keywords, operators, and other components of source code. On the other hand, pushdown automata (下推自动机) extend the capabilities of finite automata (有限自动机) by incorporating a stack data structure. This allows them to recognize context-free languages, which are essential in parsing nested structures like those found in programming languages and natural language syntax. The ability to handle recursion and nested patterns makes pushdown automata (下推自动机) a powerful tool in both theoretical and practical applications. Turing machines, introduced by Alan Turing in the 1930s, represent one of the most significant advancements in the field of automata (自动机) theory. A Turing machine consists of an infinite tape, a head that reads and writes symbols on the tape, and a set of rules that dictate its behavior. This model is capable of simulating any algorithmic process and forms the basis for our understanding of computability. The Church-Turing thesis posits that anything computable can be computed by a Turing machine, highlighting the profound implications of automata (自动机) theory in computer science. Furthermore, the application of automata (自动机) theory extends beyond theoretical constructs. In real-world scenarios, automata (自动机) are utilized in various technologies, such as search engines, compilers, and even robotics. For example, search algorithms often employ finite automata (有限自动机) to efficiently process and match queries against large datasets. Similarly, modern compilers leverage the principles of automata (自动机) theory to translate high-level programming languages into machine code, ensuring that software can run effectively on hardware. In conclusion, the study of automata (自动机) offers invaluable insights into the nature of computation and the design of efficient algorithms. As technology continues to evolve, the relevance of automata (自动机) theory will only grow, shaping the future of computer science and its applications. Understanding automata (自动机) not only enhances our ability to create sophisticated systems but also deepens our appreciation for the underlying principles that govern computation itself.