|
|
Testing Learning of Restarting Automata using Genetic Algorithm
Kovářová, Lenka ; Mráz, František (advisor) ; Černo, Peter (referee)
Title: Testing the Learning of Restarting Automata using Genetic Algorithm Author: Bc. Lenka Kovářová Department: Department of Software and Computer Science Education Supervisor: RNDr. František Mráz, CSc. Abstract: Restarting automaton is a theoretical model of device recognizing a formal language. The construction of various versions of restarting automata can be a hard work. Many different methods of learning such automata have been developed till now. Among them are also methods for learning target restarting automaton from a finite set of positive and negative samples using genetic algorithms. In this work, we propose a method for improving learning of restarting automata by means of evolutionary algorithms. The improvement consists in inserting new rules of a special form enabling adaption of the learning algorithm to the particular language. Furthermore, there is proposed a system for testing of learning algorithms for restarting automata supporting especially learning by evolutionary algorithms. A part of the work is a program for learning restarting automata using the proposed new method with a subsequent testing of discovered automata and its evaluation in a graphic form mainly. Keywords: machine learning, grammatical inference, restarting automata, genetic algorithms
|
|
|
Object Oriented Library for Controlling an e-Puck Robot
Plátek, Ondřej ; Mráz, František (advisor) ; Černo, Peter (referee)
E-Puck is an educational robot with differential drive and it is sufficiently equipped with sensors. The result of present thesis is the C# object oriented Elib library, which allows to control an e-Puck robot from a host computer over the Bluetooth wireless technology. The model examples in the TestElib console application presents the usage of the Elib library in program for the e-Puck robot. Moreover, it offers a comfortable system of help and documentation. Enclosed sets of tools allows more effective debugging of programs, which use the Elib library.
|
|
|
An environment for restarting automata
Černo, Peter ; Mráz, František (advisor) ; Hoffmann, Petr (referee)
Restarting automata are linguistically motivated models of automata that can be used e.g. in checking correctness of a sentence. The main subject of this work is to design a specialized program which allows an easy design and testing of these automata and provides specialized tools for learning finite automata and defining languages. The thesis presents theoretical background and gives formal definition of restarting automaton. Then the possibilities of implementation of such system are discussed and the actual implementation is described. The user guide is included in the thesis.
|
|
|
Clearing Restarting Automata
Černo, Peter ; Mráz, František (advisor) ; Hoffmann, Petr (referee)
Restarting automata were introduced as a model for analysis by reduction which is a linguistically motivated method for checking correctness of a sentence. The goal of the thesis is to study more restricted models of restarting automata which based on a limited context can either delete a substring of the current content of its tape or replace a substring by a special symbol, which cannot be overwritten anymore, but it can be deleted later. Such restarting automata are called clearing restarting automata. The thesis investigates the properties of clearing restarting automata, their relation to Chomsky hierarchy and possibilities for machine learning of such automata from positive and negative samples.
|
|
|
Restricted Restarting Automata
Černo, Peter ; Mráz, František (advisor) ; Kutrib, Martin (referee) ; Průša, Daniel (referee)
Restarting automata were introduced as a model for analysis by reduction which is a linguistically motivated method for checking correctness of a sentence. The thesis studies locally restricted models of restarting automata which (to the contrary of general restarting automata) can modify the input tape based only on a limited context. The investigation of such restricted models is easier than in the case of general restarting automata. Moreover, these models are effectively learnable from positive samples of reductions and their instructions are human readable. Powered by TCPDF (www.tcpdf.org)
|
|
|
Testing Learning of Restarting Automata using Genetic Algorithm
Kovářová, Lenka ; Mráz, František (advisor) ; Černo, Peter (referee)
Title: Testing the Learning of Restarting Automata using Genetic Algorithm Author: Bc. Lenka Kovářová Department: Department of Software and Computer Science Education Supervisor: RNDr. František Mráz, CSc. Abstract: Restarting automaton is a theoretical model of device recognizing a formal language. The construction of various versions of restarting automata can be a hard work. Many different methods of learning such automata have been developed till now. Among them are also methods for learning target restarting automaton from a finite set of positive and negative samples using genetic algorithms. In this work, we propose a method for improving learning of restarting automata by means of evolutionary algorithms. The improvement consists in inserting new rules of a special form enabling adaption of the learning algorithm to the particular language. Furthermore, there is proposed a system for testing of learning algorithms for restarting automata supporting especially learning by evolutionary algorithms. A part of the work is a program for learning restarting automata using the proposed new method with a subsequent testing of discovered automata and its evaluation in a graphic form mainly. Keywords: machine learning, grammatical inference, restarting automata, genetic algorithms
|
|
|
Genetic algorithms in evolutionary robotics
Mašek, Michal ; Mráz, František (advisor) ; Černo, Peter (referee)
Through series of experiments this work compares effects of different types of genetic algorithms on evolution of a neural network that is used to control a robot. Genetic algorithms using binary and real coded individuals, algorithms using basic and advanced mutations and crossovers and algorithms using fixed and variable population size are compared on three tasks of evoltionary robotics. The goal is to determine wether usage of advanced genetic algorithms leads to faster convergence or to better solution than usage of basic genetic algorithm. Experiments are performed in an easily extendable simulator developed for purposes of this work.
|
|
|
Object Oriented Library for Controlling an e-Puck Robot
Plátek, Ondřej ; Mráz, František (advisor) ; Černo, Peter (referee)
E-Puck is an educational robot with differential drive and it is sufficiently equipped with sensors. The result of present thesis is the C# object oriented Elib library, which allows to control an e-Puck robot from a host computer over the Bluetooth wireless technology. The model examples in the TestElib console application presents the usage of the Elib library in program for the e-Puck robot. Moreover, it offers a comfortable system of help and documentation. Enclosed sets of tools allows more effective debugging of programs, which use the Elib library.
|
|
|
Clearing Restarting Automata
Černo, Peter ; Mráz, František (advisor) ; Hoffmann, Petr (referee)
Restarting automata were introduced as a model for analysis by reduction which is a linguistically motivated method for checking correctness of a sentence. The goal of the thesis is to study more restricted models of restarting automata which based on a limited context can either delete a substring of the current content of its tape or replace a substring by a special symbol, which cannot be overwritten anymore, but it can be deleted later. Such restarting automata are called clearing restarting automata. The thesis investigates the properties of clearing restarting automata, their relation to Chomsky hierarchy and possibilities for machine learning of such automata from positive and negative samples.
|
|
|
An environment for restarting automata
Černo, Peter ; Hoffmann, Petr (referee) ; Mráz, František (advisor)
Restarting automata are linguistically motivated models of automata that can be used e.g. in checking correctness of a sentence. The main subject of this work is to design a specialized program which allows an easy design and testing of these automata and provides specialized tools for learning finite automata and defining languages. The thesis presents theoretical background and gives formal definition of restarting automaton. Then the possibilities of implementation of such system are discussed and the actual implementation is described. The user guide is included in the thesis.
|
guest ::
