Results 31 to 40 of about 2,128 (206)

Neuroevolution on the edge of chaos [PDF]

Proceedings of the Genetic and Evolutionary Computation Conference, 2017
Echo state networks represent a special type of recurrent neural networks. Recent papers stated that the echo state networks maximize their computational performance on the transition between order and chaos, the so-called edge of chaos. This work confirms this statement in a comprehensive set of experiments.
openaire   +4 more sources

Two-Level Genetic Algorithm for Evolving Convolutional Neural Networks for Pattern Recognition

IEEE Access, 2021
The aim of Neuroevolution is to find neural networks and convolutional neural network (CNN) architectures automatically through evolutionary algorithms.
Daniel A. Montecino, Claudio A. Perez, Kevin W. Bowyer   +2 more
doaj   +1 more source

Neuroevolutive Algorithms for Learning Gaits in Legged Robots

IEEE Access, 2019
Gait generation for legged robots is a challenging task typically requiring either a hand-tuning design or a kinematic model of the robot morphology to compute the movements, generating a high computational and time efforts.
Pablo Reyes, Maria-Jose Escobar
doaj   +1 more source

New machine behavior’s evolutionary approaches between AI learning, control and ethics promoting cooperative Human-Machine Intelligence

European Journal of Privacy Law & Technologies, 2022
The technological revolution in the fields of robotics and artificial intelligence seems to indicate a future shift in our human-centered social paradigm towards a greater inclusion of artificial cognitive agents in our everyday environments ...
Sergio Guida
doaj   +1 more source

A Study of Generalization and Fitness Landscapes for Neuroevolution

IEEE Access, 2020
Fitness landscapes are a useful concept for studying the dynamics of meta-heuristics. In the last two decades, they have been successfully used for estimating the optimization capabilities of different flavors of evolutionary algorithms, including ...
Nuno M. Rodrigues, Sara Silva, Leonardo Vanneschi   +2 more
doaj   +1 more source

Towards hardware acceleration of neuroevolution for multimedia processing applications on mobile devices [PDF]

, 2006
This paper addresses the problem of accelerating large artificial neural networks (ANN), whose topology and weights can evolve via the use of a genetic algorithm.
Daniel Larkin, O'Connor, Noel E., Larkin, Daniel, Andrew Kinane, O\u27Connor, Noel E., Noel O’Connor, Kinane, Andrew   +6 more
core   +2 more sources

Tensorial Properties via the Neuroevolution Potential Framework: Fast Simulation of Infrared and Raman Spectra. [PDF]

J Chem Theory Comput
Infrared and Raman spectroscopy are widely used for the characterization of gases, liquids, and solids, as the spectra contain a wealth of information concerning, in particular, the dynamics of these systems.
Xu N, Rosander P, Schäfer C, Lindgren E, Österbacka N, Fang M, Chen W, He Y, Fan Z, Erhart P.   +9 more
europepmc   +2 more sources

Scaling MAP-Elites to deep neuroevolution [PDF]

Proceedings of the 2020 Genetic and Evolutionary Computation Conference, 2020
Accepted to GECCO ...
Colas, Cédric, Madhavan, Vashisht, Huizinga, Joost, Clune, Jeff   +3 more
openaire   +5 more sources

Neuroevolution-based autonomous robot navigation: A comparative study

, 2020
Neuroevolution-based autonomous robot navigation: A comparative ...
S Ahmadian (13361544), MR Mahmoudi (15788264), S Nahavandi (13392411), Abbas Khosravi (13078944), SMJ Jalali (14450514), S Mirjalili (13498150)   +5 more
core   +2 more sources

Deep Hybrid Neural Network and Improved Differential Neuroevolution for Chaotic Time Series Prediction

IEEE Access, 2020
Chaos is widespread in non-linear systems such as finance, energy, and weather. In the chaos system, a variable changing with time generates a chaotic time series, which contains a wealth of information about the non-linear system, and it is helpful for ...
Weijian Huang, Yongtao Li, Yuan Huang
doaj   +1 more source