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2016 | OriginalPaper | Buchkapitel

A Free Energy Foundation of Semantic Similarity in Automata and Languages

verfasst von : Cewei Cui, Zhe Dang

Erschienen in: Similarity Search and Applications

Verlag: Springer International Publishing

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Abstract

This paper develops a free energy theory from physics including the variational principles for automata and languages and also provides algorithms to compute the energy as well as efficient algorithms for estimating the nondeterminism in a nondeterministic finite automaton. This theory is then used as a foundation to define a semantic similarity metric for automata and languages. Since automata are a fundamental model for all modern programs while languages are a fundamental model for the programs’ behaviors, we believe that the theory and the metric developed in this paper can be further used for real-word programs as well.

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Fußnoten
1
The factor 2, intuitively, comes from the fact that we “stretch”, by a factor of 2, a run in finite automaton M to correspond it to a walk in graph \({\hat{M}}\). A somewhat more efficient way to compute \({{{\mathcal {E}}}}(M_V)\) is to construct an \(m\times m\) Gurevich matrix \(\mathbf{M}'\) where m is the number of states in M such that \(\mathbf{M}'_{ij}=0\) if there is no transition from \(p_i\) to \(p_j\) in M, else \(\mathbf{M}'_{ij}=\sum _{a:(p_i,a,p_j)\in T} e^{V(p_i,a,p_j)}\). Herein, \(p_1,\cdots , p_m\) are all states in M. One can show that \({{{\mathcal {E}}}}(M_V)=\ln \lambda '\) where \(\lambda '\) is the Perron-Frobenius eigenvalue of \(\mathbf{M}'\). We omit the details.
 
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Metadaten
Titel
A Free Energy Foundation of Semantic Similarity in Automata and Languages
verfasst von
Cewei Cui
Zhe Dang
Copyright-Jahr
2016
DOI
https://doi.org/10.1007/978-3-319-46759-7_3

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