Name
Abstract | ||
|---|---|---|
Twelve years have passed since the advent of grammatical evolution (GE) in 1998, but such issues as vast search space, genotypic readability, and the inherent relationship among grammatical concepts, production rules and derivations have remained untouched in almost all existing GE researches. Model-based approach is an attractive method to achieve different objectives of software engineering. In this paper, we make the first attempt to model syntactically usable information of GE using an automaton, coming up with a novel solution called model-based grammatical evolution (MGE) to these problems. In MGE, the search space is reduced dramatically through the use of concepts from building blocks, but the functionality and expressiveness are still the same as that of classical GE. Besides, complex evolutionary process can visually be analyzed in the context of transition diagrams. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1007/s11432-011-4411-8 | SCIENCE CHINA Information Sciences |
Keywords | Field | DocType |
genetic programming,grammatical evolution,finite state automaton,model | USable,Computer science,Genetic programming,Theoretical computer science,Artificial intelligence,Natural language processing,Computer programming,Expressivity,Mathematical optimization,Automaton,Finite-state machine,Readability,Grammatical evolution | Journal |
Volume | Issue | ISSN |
54 | 12 | null |
Citations | PageRank | References |
4 | 0.44 | 14 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Pei He | 1 | 4 | 0.44 |
| Colin G. Johnson | 2 | 933 | 115.57 |
| Hou-Feng Wang | 3 | 611 | 53.83 |