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 evolutio...
详细信息
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. Copyright (C) 2009 Z. Oplatkova and I. Zelinka. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
暂无评论