Neuroevolution

Neuroevolution, or neuro-evolution, is a form of machine learning that uses evolutionary algorithms to train artificial neural networks. It is most…

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.

2020

Fitness landscapes are a useful concept to study the dynamics of meta-heuristics. In the last two decades, they have been applied…

2017

Among the issues discussed in this article the main problem concerns a neuro-fuzzy system (ANFIS) for controlling a mobile robot…

2013

The ordinary differential evolution (DE) algorithm employs real-valued vectors as genotypes. The author previously proposed an…

2012

Communication through vocalizations is used by spotted hyenas and chimpanzees for coordination during hunting and for raising…

2012

Evolutionary learning of neural networks, i.e., neuroevolution, has shown to play an important role in agent constitutions. It…

2009

This paper explores the idea that auto-teaching neural networks with evolved selfsupervision signals can lead to improved…

2008

Studying the diversity of genetic algorithms is the most important topic to prevent the problem of premature convergence of the…

2008

For many complex Reinforcement Learning (RL) problems with large and continuous state spaces, neuroevolution has achieved…

2005

2005

An oxygen absorbent comprising a metal powder and a metal halide coated thereon is disclosed.