Evolutionary algorithms (EAs) have been successfully applied to optimize the policies for Reinforcement Learning (RL) tasks due their exploration ability. The recently proposed Negatively Correlated Search (NCS) provides a distinct parallel search behavior and is expected facilitate RL more effectively. Considering that commonly adopted neural usually involves millions of parameters be optimize...

Abstract: One of the equipment that can help improve distribution system status today and reduce the cost of fault time is remote control switches (RCS). Finding the optimal location and number of these switches in the distribution system can be modeled with various objective functions as a nonlinear optimization problem to improve system reliability and cost. In this article, a particle swarm ...

concept analysis of transition from nursing student to clinical nurse: rodgers' evolutionary concept analysis     rafieef [1] , sajadihezaveh m [2] *     received: 21 feb, 2012 accepted: 27apr, 2012     abstract   background &aims; : the transition from nursing student to clinical nursing is a major challenge.the aim of this study was to clarify concept of transition in new graduate nursin...

There are various automatic programming models inspired by evolutionary computation techniques. Due to the importance of devising an automatic mechanism to explore the complicated search space of mathematical problems where numerical methods fails, evolutionary computations are widely studied and applied to solve real world problems. One of the famous algorithm in optimization problem is shuffl...

Gaphyl is an application of evolutionary algorithms (EA’s) to phylogenetics, an approach used by biologists to investigate evolutionary relationships among organisms. For datasets larger than 20-30 species, exhaustive search is not practical in this domain. Gaphyl uses an evolutionary search mechanism to search the space of possible phylogenetic trees, in an attempt to find the most plausible e...

Evolutionary computation has become an important problem solving methodology among the set of search and optimization techniques. Recently, more and more different evolutionary techniques have been developed, especially hybrid evolutionary algorithms. This paper proposes an island based hybrid evolutionary algorithm (IHEA) for optimization, which is based on Particle swarm optimization (PSO), F...

This paper introduces a discussion about evolutionary search methods based on Hamming oracle. In many optimization problems, the design of the fitness function includes the Hamming distance being referred this kind of functions as Hamming oracle. In this paper we adopt a critical look and ask ourselves to what extent genetic algorithms and other related evolutionary methods truly mimic evolutio...

Many frustrating experiences have been encountered when the training of neural networks by local search methods becomes stagnant at local optima. This calls for the development of more satisfactory search methods such as evolutionary search. However, training by evolutionary search can require a long computation time. In certain situations, using Lamarckian evolution, local search and evolution...