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The StaMinA Competition - Learning regular languages with large alphabets

The STAMINA (STAte Machine INference Approaches) competition aims to identify the best technique for learning deterministic finite state machines. It extends former competitions, especially Abbadingo, and focusses on the complexity of the learning with respect to the alphabet size. Stamina relies on original generation protocols for target machines and learning samples. It aims to encourage the development of novel learning algorithms and to encourage cross-fertilization between the machine learning and sof

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The StaMinA Competition - Learning regular languages with large alphabets | stamina.chefbe.net Reviews

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The STAMINA (STAte Machine INference Approaches) competition aims to identify the best technique for learning deterministic finite state machines. It extends former competitions, especially Abbadingo, and focusses on the complexity of the learning with respect to the alphabet size. Stamina relies on original generation protocols for target machines and learning samples. It aims to encourage the development of novel learning algorithms and to encourage cross-fertilization between the machine learning and sof

<META> KEYWORDS

1 grammar inference

2 grammar induction

3 grammatical inference

4 learning competition

5 learning contest

6 learning algorithm

7 final state machine

8 dfa

9 automaton

10 software engineering

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any question,create an account,protocol,participate,download,baseline,scientific committee,the stamina competition,news,register and participate,the stamina organizers,the stamina,see also instructions,the competition ended,marijn heule,with the dfasat

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The StaMinA Competition - Learning regular languages with large alphabets | stamina.chefbe.net Reviews

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The STAMINA (STAte Machine INference Approaches) competition aims to identify the best technique for learning deterministic finite state machines. It extends former competitions, especially Abbadingo, and focusses on the complexity of the learning with respect to the alphabet size. Stamina relies on original generation protocols for target machines and learning samples. It aims to encourage the development of novel learning algorithms and to encourage cross-fertilization between the machine learning and sof

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The StaMinA Competition - Baseline

http://stamina.chefbe.net/baseline

Learning regular languages with large alphabets. Open-source code of RPNI. And Blue-Fringe is proposed as a good starting point for challengers. This code is written in Ruby and distributed under a MIT. Download, sources and api. Download the stable version 0.2.1. Documentation of version 0.2.1. This code is also made available through Subversion (read-only), if you prefer working ‘on-the-edge’ or plan to submit patches. You can download the trunk version of the source code using:. Rake test rake rerdoc.

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The StaMinA Competition - Download

http://stamina.chefbe.net/download

Learning regular languages with large alphabets. Training and Test Sets. Training and test strings for each of the 100 problems can be downloaded using the two tables below. A cell is considered broken if your induction algorithm solves the 5 problems it contains (see the protocol page. For details, and the section below. Alternatively to these tables, you can download the .tar.gz archive. That contains all of the training and test sets:. Sparsity of the training sample. Sparsity of the training sample.

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The StaMinA Competition - Scientific Committee

http://stamina.chefbe.net/committee

Learning regular languages with large alphabets. University of Amsterdam, The Netherlands. The University of Sheffield, UK. Université catholique de Louvain, Louvain-la-Neuve, Belgium. Université catholique de Louvain, Louvain-la-Neuve, Belgium. Université Charles de Gaulle – Lille 3, France. Iowa State University of Science and Technology, USA. Université catholique de Louvain, Louvain-la-Neuve, Belgium. National University of Singapore, Republic of Singapore. University of Milan Bicocca, Italy.

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The StaMinA Competition - Competition protocol

http://stamina.chefbe.net/protocol

Learning regular languages with large alphabets. This page describes the competition protocol in details. It also provides information about the target machines. The training and test samples. Of submitted test results. The competition server has a total of 100 problems. 8211; each problem is a sample of positive and negative strings generated by randomly walking a target machine. These problems vary in terms of their difficulty, related to. The size of the alphabet. In the target machine. 1 – 5. Of at l...

5

The StaMinA Competition - How to participate ?

http://stamina.chefbe.net/participate

Learning regular languages with large alphabets. The aim of the competition is to identify the most successful technique for learning state machines from samples. Of their behaviour. In other words, given a set of strings that are classified as either positive (i.e. they are accepted by the target machine) or negative (they are rejected), the learned model should accurately classify new strings as positive and negative. Participation in the competition consists in attempting to solve.

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grammarlearning.org

Competitions | grammarlearning.org

https://grammarlearning.org/node/11

Skip to main content. Home of the International Community interested in Grammatical Inference. In addition to formal grammatical inference, which focuses on formal proofs of learnability of classes of languages under certain conditions, there is also research in the area of empirical grammatical inference. In this field, the aim is to learn a particular grammar (not necessarily a class of grammars). Additional difficulties may be introduced, such as noise. The Abbadingo One Learning Competition. In 1996,...

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The StaMinA Competition - Learning regular languages with large alphabets

Learning regular languages with large alphabets. As you’ll see below, the Stamina competition is now closed. Congratulations to the winners once again! However, we are currently in the process of updating this website to become an online benchmark for grammar induction (applied to software model synthesis). This means that you can still download training and test sets. Use the oracle (once registered), and … try to outperform the winning algorithm. Our new benchmarking oracle. Feel free to contact. The m...

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