National Repository of Grey Literature 2 records found  Search took 0.01 seconds. 
Jumping Formal Models Inference
Heindlová, Tina ; Bidlo, Michal (referee) ; Křivka, Zbyněk (advisor)
This thesis is focused on grammatical inference in the way of evolutionary algorithms for jumping finite models. The first part explains jumping finite models as itself. More specifically, it describes jumping grammars and jumping automata. The next part deals with grammatical inference, evolutionary algorithms, and their important parts. According to the developed jumping models, said parts include strings generation and membership testing. These two algorithms are applied to chosen types of jumping finite automata---jumping finite automata, general jumping finite automata, and right one-way jumping finite automata. These four types of automata were tested, and in total, sixteen experiments were run. Results show that the inference works much better for automata without branching and with a small number of states and a small alphabet.
Jumping Formal Models Inference
Heindlová, Tina ; Bidlo, Michal (referee) ; Křivka, Zbyněk (advisor)
This thesis is focused on grammatical inference in the way of evolutionary algorithms for jumping finite models. The first part explains jumping finite models as itself. More specifically, it describes jumping grammars and jumping automata. The next part deals with grammatical inference, evolutionary algorithms, and their important parts. According to the developed jumping models, said parts include strings generation and membership testing. These two algorithms are applied to chosen types of jumping finite automata---jumping finite automata, general jumping finite automata, and right one-way jumping finite automata. These four types of automata were tested, and in total, sixteen experiments were run. Results show that the inference works much better for automata without branching and with a small number of states and a small alphabet.

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