AbstractThe course of socio-cultural transition can neither be aimless nor arbitrary, instead it requires a clear direction. A common goal of social species’ evolution is to move towards an advanced spiritual and conscious state. This study aims to develop a population-based algorithm on the basis of cultural transition goal. In this paper, the socio-cultural model based on a system thought framework could be used to develop a cultural evolution algorithm (CEA). CEA leverage four strategies, each consists of several search methods with similar thinking. Seven benchmark functions are utilized to validate the search performance of the proposed algorithm. The results show that all of the four strategies of cultural evolution algorithm have bet...
Human culture is the accumulation and evolution of results produced by countless design exercises. H...
Abstract - Various biologically inspired approaches to problem solving using a social metaphor have ...
AbstractThe main weak points in using AI optimization technique are the possibility of being trapped...
AbstractThe course of socio-cultural transition can neither be aimless nor arbitrary, instead it req...
Optimization problems is a class of problems where the goal is to make a system as effective as poss...
The optimization of dynamic problems is both widespread and diffi-cult. When conducting dynamic opti...
Cultural Algorithm (CA) is one of the Evolutionary Algorithms (EAs) which de- rives from the cultura...
Explaining the origins of cumulative culture, and how it is maintained over long timescales, constit...
Copyright © 2014 Carolina Lagos et al.This is an open access article distributed under the Creative ...
Traditionally, the Evolutionary Computation (EC) paradigm is inspired by Darwinian evolution or the ...
In this paper, we propose the use of a cultural algorithm combined with evolutionary programming to ...
The speed and transformative power of human cultural evolution is evident from the change it has wro...
Evolutionary Algorithms (EAs) are meta-heuristic algorithms used for optimization of complex problem...
Population evolution algorithms such as Cultural Algorithms (CA) enable a global repository known as...
Over the last few decades, a plethora of improved evolutionary algorithms was developed with exquisi...
Human culture is the accumulation and evolution of results produced by countless design exercises. H...
Abstract - Various biologically inspired approaches to problem solving using a social metaphor have ...
AbstractThe main weak points in using AI optimization technique are the possibility of being trapped...
AbstractThe course of socio-cultural transition can neither be aimless nor arbitrary, instead it req...
Optimization problems is a class of problems where the goal is to make a system as effective as poss...
The optimization of dynamic problems is both widespread and diffi-cult. When conducting dynamic opti...
Cultural Algorithm (CA) is one of the Evolutionary Algorithms (EAs) which de- rives from the cultura...
Explaining the origins of cumulative culture, and how it is maintained over long timescales, constit...
Copyright © 2014 Carolina Lagos et al.This is an open access article distributed under the Creative ...
Traditionally, the Evolutionary Computation (EC) paradigm is inspired by Darwinian evolution or the ...
In this paper, we propose the use of a cultural algorithm combined with evolutionary programming to ...
The speed and transformative power of human cultural evolution is evident from the change it has wro...
Evolutionary Algorithms (EAs) are meta-heuristic algorithms used for optimization of complex problem...
Population evolution algorithms such as Cultural Algorithms (CA) enable a global repository known as...
Over the last few decades, a plethora of improved evolutionary algorithms was developed with exquisi...
Human culture is the accumulation and evolution of results produced by countless design exercises. H...
Abstract - Various biologically inspired approaches to problem solving using a social metaphor have ...
AbstractThe main weak points in using AI optimization technique are the possibility of being trapped...