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178
Derivatives of regular expressions
 JOURNAL OF THE ACM
, 1964
"... Abstract. Kleene's regular expressions, which can be used for describing sequential circuits, were defined using three operators (union, concatenation and iterate) on sets of sequences. Word descriptions of problems can be more easily put in the regular expression language if the language is en ..."
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Cited by 273 (11 self)
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Abstract. Kleene's regular expressions, which can be used for describing sequential circuits, were defined using three operators (union, concatenation and iterate) on sets of sequences. Word descriptions of problems can be more easily put in the regular expression language if the language is enriched by the inclusion of other logical operations. However, in the problem of converting the regular expression description to a state diagram, the existing methods either cannot handle expressions with additional operators, or are made quite complicated by the presence of such operators. In this paper the notion of a derivative of a regular expression is introduced and the properties of derivatives are discussed. This leads, in a very natural way, to the construction of a state diagram from a regular expression containing any number of logical operators.
Inductive Inference, DFAs and Computational Complexity
 2nd Int. Workshop on Analogical and Inductive Inference (AII
, 1989
"... This paper surveys recent results concerning the inference of deterministic finite automata (DFAs). The results discussed determine the extent to which DFAs can be feasibly inferred, and highlight a number of interesting approaches in computational learning theory. 1 ..."
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Cited by 91 (1 self)
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This paper surveys recent results concerning the inference of deterministic finite automata (DFAs). The results discussed determine the extent to which DFAs can be feasibly inferred, and highlight a number of interesting approaches in computational learning theory. 1
Toward formal development of ML programs: foundations and methodology
, 1989
"... A formal methodology is presented for the systematic evolution of modular Standard ML programs from specifications by means of verified refinement steps, in the framework of the Extended ML specification language. Program development proceeds via a sequence of design (modular decomposition), codi ..."
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Cited by 54 (23 self)
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A formal methodology is presented for the systematic evolution of modular Standard ML programs from specifications by means of verified refinement steps, in the framework of the Extended ML specification language. Program development proceeds via a sequence of design (modular decomposition), coding and refinement steps. For each of these three kinds of steps, conditions are given which ensure the correctness of the result. These conditions seem to be as weak as possible under the constraint of being expressible as "local" interface matching requirements. Interfaces are only required to match up to behavioural equivalence, which is seen as vital to the use of data abstraction in program development. Copyright c fl 1989 by D. Sannella and A. Tarlecki. All rights reserved. An extended abstract of this paper will appear in Proc. Colloq. on Current Issues in Programming Languages, Joint Conf. on Theory and Practice of Software Development (TAPSOFT), Barcelona, Springer LNCS (1989)....
Tree Exploration with Little Memory
 SODA'02
, 2002
"... A robot with kbit memory has to explore a tree whose nodes are unlabeled and edge ports are locally labeled at each node. The robot has no a priori knowledge of the topology of the tree or of its size, and its aim is to traverse all the edges. While O(log ) bits of memory suce to explore any tre ..."
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Cited by 53 (21 self)
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A robot with kbit memory has to explore a tree whose nodes are unlabeled and edge ports are locally labeled at each node. The robot has no a priori knowledge of the topology of the tree or of its size, and its aim is to traverse all the edges. While O(log ) bits of memory suce to explore any tree of maximum degree if stopping is not required, we show that bounded memory is not sucient to explore with stop all trees of bounded degree (indeed nde log log n) bits of memory are needed for some such trees of size n). For the more demanding task requiring to stop at the starting node after completing exploration, we show a sharper lower bound nd n) on required memory size, and present an algorithm to accomplish this task with O(log n)bit memory, for all nnode trees.
Distinguishing Tests for Nondeterministic and Probabilistic Machines
, 1995
"... We study the problem of uniquely identifying the initial state of a given finitestate machine from among a set of possible choices, based on the inputoutput behavior. Equivalently, given a set of machines, the problem is to design a test that distinguishes among them. We consider nondeterministic ..."
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Cited by 43 (3 self)
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We study the problem of uniquely identifying the initial state of a given finitestate machine from among a set of possible choices, based on the inputoutput behavior. Equivalently, given a set of machines, the problem is to design a test that distinguishes among them. We consider nondeterministic machines as well as probabilistic machines. In both cases, we show that it is Pspacecomplete to decide whether there is a preset distinguishing strategy (i.e. a sequence of inputs fixed in advance), and it is Exptimecomplete to decide whether there is an adaptive distinguishing strategy (i.e. when the next input can be chosen based on the outputs observed so far). The probabilistic testing is closely related to probabilistic games, or Markov Decision Processes, with incomplete information. We also provide optimal bounds for deciding whether such games have strategies winning with probability 1. 1 Introduction Finitestate machines have been widely used to model systems in diverse areas o...
Generating Grammars for Structured Documents Using Grammatical Inference Methods
, 1996
"... Dictionaries, user manuals, encyclopedias, and annual reports are typical examples of structured documents. Structured documents have an internal, usually hierarchical, organization that can be used, for instance, to help in retrieving information from the documents and in transforming documents int ..."
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Cited by 42 (4 self)
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Dictionaries, user manuals, encyclopedias, and annual reports are typical examples of structured documents. Structured documents have an internal, usually hierarchical, organization that can be used, for instance, to help in retrieving information from the documents and in transforming documents into another form. The document structure is typically represented by a contextfree or regular grammar. Many structured documents, however, lack the grammar: the structure of individual documents is known but the general structure of the document class is not available. Examples of this kind of documents include documents that have Standard Generalized Markup Language (SGML) tags but not a Document Type Definition (DTD). In this thesis we present a technique for generating a grammar describing the structure of a given structured document instances. The technique is based on ideas from machine learning. It forms first finitestate automata describing the given instances completely. These automata ...
Inferring Finite Automata with Stochastic Output Functions and an Application to Map Learning
, 1995
"... It is often useful for a robot to construct a spatial representation of its environment from experiments and observations, in other words, to learn a map of its environment by exploration. In addition, robots, like people, make occasional errors in perceiving the spatial features of their environmen ..."
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Cited by 41 (4 self)
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It is often useful for a robot to construct a spatial representation of its environment from experiments and observations, in other words, to learn a map of its environment by exploration. In addition, robots, like people, make occasional errors in perceiving the spatial features of their environments. We formulate map learning as the problem of inferring from noisy observations the structure of a reduced deterministic finite automaton. We assume that the automaton to be learned has a distinguishing sequence. Observation noise is modeled by treating the observed output at each state as a random variable, where each visit to the state is an independent trial and the correct output is observed with probability exceeding 1=2. We assume no errors in the state transition function. Using this framework, we provide an exploration algorithm to learn the correct structure of such an automaton with probability 1 \Gamma ffi , given as inputs ffi , an upper bound m on the number of states, a disti...
Operational congruences for reactive systems
, 2001
"... This document consists of a slightly revised and corrected version of a dissertation ..."
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Cited by 35 (4 self)
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This document consists of a slightly revised and corrected version of a dissertation