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.
This paper presents an idea of new algorithm combining advantages of evolutionary algorithm and simple distributed computing to perform tasks which required many re-runs of the same program. Computing lime is shorted ...
详细信息
ISBN:
(纸本)9780955301858
This paper presents an idea of new algorithm combining advantages of evolutionary algorithm and simple distributed computing to perform tasks which required many re-runs of the same program. Computing lime is shorted due to elementary distribution within a number of common computers via the Internet. Progressive .NET Framework technology allowing this algorithm to run effectively and examples of possible usage are also described. The algorithm deals with a problem of synthesis of the artificial neural networks using the evolutional scanning method. The basic task to be solved is to create a symbolic regression algorithm on principles of analytic programming, which will be capable of performing a convenient neural network synthesis. The main motivation here is the computerization of such synthesis and discovering so far unknown solutions.
This work deals with a problem of synthesis of the artificial neural networks using the evolutional scanning method. The basic task to be solved is to create a symbolic regression algorithm on principles of analytic p...
详细信息
ISBN:
(纸本)9780955301827
This work deals with a problem of synthesis of the artificial neural networks using the evolutional scanning method. The basic task to be solved is to create a symbolic regression algorithm on principles of analytic programming, which will be capable of performing a convenient neural network synthesis. The main motivation here is the computerization of such synthesis and discovering so far unknown solutions.
The paper deals with a novelty tool for symbolic regression - analytic programming (AP) which is able to solve various problems from the symbolic regression domain. One of tasks for it can be setting an optimal trajec...
详细信息
ISBN:
(纸本)0955301807
The paper deals with a novelty tool for symbolic regression - analytic programming (AP) which is able to solve various problems from the symbolic regression domain. One of tasks for it can be setting an optimal trajectory for artificial ant on Santa Fe trail which is main application of analytic programming in this paper. In this contribution main principles of AP are described and explained. In second part of the article how AP was used for setting an optimal trajectory for artificial ant according the user requirements is in detail described. An ability to create so called programms, as well as Genetic programming (GP) or Grammatical Evolution (GE) do, is shown in that part. AP is a superstructure of evolutionary algorithms wich are necessary to run AP. In this contribution Simulated Annealing as an evolutionary algorithm was used to carry preliminary simulations out.
暂无评论