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Learning Probabilistic Residual Finite State Automata
[chapter]
2002
Lecture Notes in Computer Science
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We introduce a new class of probabilistic automata: Probabilistic Residual Finite State Automata. ...
We prove that there are more languages generated by PRFA than by Probabilistic Deterministic Finite Automata (PDFA). ...
Probabilistic residual finite state automata (PRFA) We introduce in this section the class of probabilistic residual finite state automata (PRFA). ...
doi:10.1007/3-540-45790-9_7
fatcat:go6ap7enwjhnflnwve4ayalj74
Residuality and Learning for Nondeterministic Nominal Automata
[article]
2022
arXiv
pre-print
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This property enables active learning algorithms, and makes up for the fact that residuality -- a semantic property -- is undecidable for nominal automata. ...
To answer it, we develop the theory of residual nominal automata, a subclass of nondeterministic nominal automata. ...
We thank Borja Balle for references on residual probabilistic languages, and Henning Urbat for discussions on nominal lattice theory. ...
arXiv:1910.11666v7
fatcat:w2qd6tv4o5hypbhu62urhlluwu
Residuality and Learning for Nondeterministic Nominal Automata
2022
Logical methods in computer science : LMCS 18(1)
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This property enables active learning algorithms, and makes up for the fact that residuality -a semantic property -is undecidable for nominal automata. ...
To answer it, we develop the theory of residual nominal automata, a subclass of nondeterministic nominal automata. ...
We thank Borja Balle for references on residual probabilistic languages, and Henning Urbat for discussions on nominal lattice theory. ...
doi:10.18154/rwth-2022-01916
fatcat:lyzgpncm7jcr5ijewbmsmknpey
PAutomaC: a probabilistic automata and hidden Markov models learning competition
2013
Machine Learning
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The Probabilistic Automata learning Competition (PAutomaC), run in 2012, was the first grammatical inference challenge that allowed the comparison between these methods and algorithms. ...
grammars and finite state machines and the relevant literature. ...
residual finite state automata (Prfa) [31] , and multiplicity automata (Ma) [9, 8] (or weighted automata [54] ). ...
doi:10.1007/s10994-013-5409-9
fatcat:ey3ghvxqxzbevmpzxmv5tytvay
Active Automata Learning in Practice
[chapter]
2018
Lecture Notes in Computer Science
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Five years ago (in 2011) we have surveyed the then current state of active automata learning research and applications of active automata learning in practice. ...
Active automata learning is slowly becoming a standard tool in the toolbox of the software engineer. ...
finite state automata. ...
doi:10.1007/978-3-319-96562-8_5
fatcat:jtpzftrzvzf3tdtbncntfc4s4q
Links between probabilistic automata and hidden Markov models: probability distributions, learning models and induction algorithms
2005
Pattern Recognition
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On the other hand, HMMs with final probabilities and probabilistic automata generate distributions over strings of finite length. ...
A semi-probabilistic automaton 2 (semi-PA) is a 5-tuple , Q, , , where is a finite alphabet, Q is a finite set of states, : Q × × Q → [0, 1] is a mapping defining the transition probability function, : ...
Esposito et al. study the identification of probabilistic residual finite state automata (PRFA). The PRFA class includes properly the PDFA class and is strictly included in the PNFA class [45] . ...
doi:10.1016/j.patcog.2004.03.020
fatcat:uytkvkyfpfbj3lhibry6cfwue4
Some Classes of Regular Languages Identifiable in the Limit from Positive Data
[chapter]
2002
Lecture Notes in Computer Science
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Probabilistic Residual Finite State Automata
p. 77
Fragmentation: Enhancing Identifiability
p. 92
On Limit Points for Some Variants of Rigid Lambek Grammars
p. 106
Generalized Stochastic Tree ...
Automata for Multi-relational Data Mining
p. 120
On Sufficient Conditions to Identify Classes of Grammars from Polynomial Time and Data p. 134
Stochastic Grammatical Inference with Multinomial Tests ...
doi:10.1007/3-540-45790-9_6
fatcat:nmlknwqoyfbybhb6rpomqrn7qy
Learning Classes of Probabilistic Automata
[chapter]
2004
Lecture Notes in Computer Science
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Probabilistic finite automata (PFA) model stochastic languages, i.e. probability distributions over strings. Inferring PFA from stochastic data is an open field of research. ...
Finally, we propose a learning algorithm for a subclass of PFA, called PRFA. ...
Probabilistic Residual Finite Automata Definition 2 (Probabilistic Residual Finite Automaton). ...
doi:10.1007/978-3-540-27819-1_9
fatcat:e5cxnbd3drb73m55w3jflpttbu
Rational stochastic languages
[article]
2006
arXiv
pre-print
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We define the notion of residual of a stochastic language and we use it to investigate properties of several subclasses of rational stochastic languages. ...
Lastly, we study the representation of rational stochastic languages by means of multiplicity automata. ...
Residual Automata (PRA), i.e. probabilistic automata whose structure is a residual finite state automaton (RFSA) [CO94, CO99, dlHT00, ELDD02, DE04] . ...
arXiv:cs/0602093v1
fatcat:4gz4cyxfqber3f5puh5gpljwx4
How to measure the topological quality of protein grammars?
[article]
2017
arXiv
pre-print
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Context-free and context-sensitive formal grammars are often regarded as more appropriate to model proteins than regular level models such as finite state automata and Hidden Markov Models. ...
In theory, the claim is well founded in the fact that many biologically relevant interactions between residues of protein sequences have a character of nested or crossed dependencies. ...
Context-free (CF) and context-sensitive (CS) formal grammars are often regarded as more appropriate to model proteins than regular level models such as finite state automata and Hidden Markov Models (HMM ...
arXiv:1611.10078v2
fatcat:eunzyetdwnaqdndmzn5ufnw7ke
Using Pseudo-Stochastic Rational Languages in Probabilistic Grammatical Inference
[article]
2008
arXiv
pre-print
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The estimate of P stands in some class of probabilistic models such as probabilistic automata (PA). In this paper, we focus on probabilistic models based on multiplicity automata (MA). ...
In probabilistic grammatical inference, a usual goal is to infer a good approximation of an unknown distribution P called a stochastic language. ...
A new state will be added to the automaton if the residual language corresponding to (ux) −1 p s cannot be approximated as a linear combination of the residual languages corresponding the states already ...
arXiv:cs/0607085v2
fatcat:2x3xe6svgfdevg67o2m6mwf4pi
Learning Probability Distributions Generated by Finite-State Machines
[chapter]
2016
Topics in Grammatical Inference
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The methods we review are state merging and state splitting methods for probabilistic deterministic automata and the recently developed spectral method for nondeterministic probabilistic automata. ...
to account for the error introduced by a finite sample. ...
Probabilistic Automata A probabilistic finite automaton (pfa) of size n is a tuple Q, Σ , τ, α 0 , α ∞ where Q is a set of n states, Σ is a finite alphabet, τ : Q × Σ × Q → [0, 1] is the transition probability ...
doi:10.1007/978-3-662-48395-4_5
fatcat:u4cepbpghjcv7ct6zoqrgir2cy
Compositional Stochastic Model Checking Probabilistic Automata via Assume-guarantee Reasoning
2020
International Journal of Networked and Distributed Computing (IJNDC)
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is a popular active learning algorithm (since they can ask queries actively) for Residual Finite-State Automata (RFSA) [35, 36] . ...
Generally, the RFSA may generate extra nondeterministic choices in the product PA [37] and it is a subclass of Nondeterministic Finite-state Automata (NFA). ...
doi:10.2991/ijndc.k.190918.001
fatcat:55ee6cvpp5btfdox3qg7qezyci
Using Pseudo-stochastic Rational Languages in Probabilistic Grammatical Inference
[chapter]
2006
Lecture Notes in Computer Science
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The estimate of P stands in some class of probabilistic models such as probabilistic automata (PA). In this paper, we focus on probabilistic models based on multiplicity automata (MA). ...
In probabilistic grammatical inference, a usual goal is to infer a good approximation of an unknown distribution P called a stochastic language. ...
A new state will be added to the automaton if the residual language corresponding to (ux) −1 p s cannot be approximated as a linear combination of the residual languages corresponding the states already ...
doi:10.1007/11872436_10
fatcat:zhpwf32bpngahkxkwcqblwg6qq
Automated Learning of Probabilistic Assumptions for Compositional Reasoning
[chapter]
2011
Lecture Notes in Computer Science
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We do so using algorithmic learning techniques, which have already proved to be successful for the generation of assumptions for compositional verification of non-probabilistic systems. ...
We discuss recent developments in the area of automated compositional verification techniques for probabilistic systems. ...
Whereas L* learns a minimal DFA for a regular language, the algorithm NL* [7] learns a minimal residual finite-state automaton (RFSA). RFSAs are a subclass of nondeterministic finite automata. ...
doi:10.1007/978-3-642-19811-3_2
fatcat:ghpdevjwxndgrhjo35deeqxgeq
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