- author = "Zuzana Oplatkova and Ivan Zelinka",
- title = "Investigation on Evolutionary Synthesis of Movement Commands",
- journal = "Modelling and Simulation in Engineering",
- year = "2009",
- keywords = "genetic algorithms, genetic programming",
- ISSN = "16875591",
-
URL = "
http://downloads.hindawi.com/journals/mse/2009/845080.pdf",
-
DOI = "
doi:10.1155/2009/845080",
- bibsource = "OAI-PMH server at www.doaj.org",
- language = "eng",
- oai = "oai:doaj-articles:3407db6981a4f0793fa9cea5d37ff9a1",
- broken = "http://www.doaj.org/doaj?func=openurl\&genre=article\&issn=16875591\&date=2009\&volume=2009\&issue=\&spage=",
- publisher = "Hindawi Publishing Corporation",
- abstract = "This paper deals with usage of an alternative tool for symbolic regression---analytic programming which is able to solve various problems from the symbolic domain, as well as genetic programming and grammatical evolution. This paper describes a setting of an optimal trajectory for a robot (originally designed as an artificial ant on Santa Fe trail) solved by means of analytic programming. Firstly, main principles of analytic programming are described and explained. The second part shows how analytic programming was used for the application of finding a suitable trajectory step by step. Because analytic programming needs evolutionary algorithms for its run, three evolutionary algorithms were used---self-organizing migrating algorithm, differential evolution, and simulated annealing---to show that anyone can be used. The total number of simulations was 150 and results show that the first two used algorithms were more successful than not so robust simulated annealing.",
-
notes = "Article ID 845080
Faculty of Applied Informatics, Tomas Bata University in Zlin, Nad Stranemi 4511, 762 72 Zlin, Czech Republic",
