Bideterministic weighted automata

IF 0.8 4区 计算机科学 Q3 COMPUTER SCIENCE, THEORY & METHODS
Peter Kostolányi
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引用次数: 0

Abstract

A finite automaton is called bideterministic if it is both deterministic and codeterministic – that is, if it is deterministic and its transpose is deterministic as well. The study of such automata in a weighted setting is initiated. All trim bideterministic weighted automata over integral domains and over positive semirings are proved to be minimal. On the contrary, it is observed that this property does not hold over commutative rings in general: non-minimal trim bideterministic weighted automata do exist over all semirings that are not zero-divisor free, and over many such semirings, these automata might not even admit equivalents that are both minimal and bideterministic. The problem of determining whether a given rational series is realised by a bideterministic automaton is shown to be decidable over fields and over tropical semirings. An example of a positive semiring over which this problem becomes undecidable is given as well.

双确定性加权自动机
如果有限自动机既是确定性的又是共确定性的——也就是说,如果它是确定性的,并且它的转置也是确定性的,那么它就被称为双确定性的。开始了对加权设置中的这种自动机的研究。证明了积分域上和正半环上的所有修剪双定权自动机都是极小的。相反,我们观察到这个性质在一般交换环上不成立:非极小修剪双确定加权自动机确实存在于所有非零除数自由的半环上,并且在许多这样的半环中,这些自动机甚至可能不允许同时是极小和双确定的等价物。证明了确定给定有理级数是否由双定自动机实现的问题在域和热带半环上是可判定的。给出了一个正半环的例子,在这个半环上这个问题是不可判定的。
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来源期刊
Information and Computation
Information and Computation 工程技术-计算机:理论方法
CiteScore
2.30
自引率
0.00%
发文量
119
审稿时长
140 days
期刊介绍: Information and Computation welcomes original papers in all areas of theoretical computer science and computational applications of information theory. Survey articles of exceptional quality will also be considered. Particularly welcome are papers contributing new results in active theoretical areas such as -Biological computation and computational biology- Computational complexity- Computer theorem-proving- Concurrency and distributed process theory- Cryptographic theory- Data base theory- Decision problems in logic- Design and analysis of algorithms- Discrete optimization and mathematical programming- Inductive inference and learning theory- Logic & constraint programming- Program verification & model checking- Probabilistic & Quantum computation- Semantics of programming languages- Symbolic computation, lambda calculus, and rewriting systems- Types and typechecking
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