Skip to search form
Skip to main content
Skip to account menu
Semantic Scholar
Semantic Scholar's Logo
Search 236,983,674 papers from all fields of science
Search
Sign In
Create Free Account
HyperNEAT
Hypercube-based NEAT, or HyperNEAT, is a generative encoding that evolves artificial neural networks (ANNs) with the principles of the widely used…
Expand
Wikipedia
(opens in a new tab)
Create Alert
Alert
Related topics
Related topics
4 relations
Compositional pattern-producing network
Neuroevolution
Neuroevolution of augmenting topologies
Broader (1)
Evolutionary computation
Papers overview
Semantic Scholar uses AI to extract papers important to this topic.
2018
2018
Embodied Embeddings for Hyperneat
C. Cappelle
,
J. Bongard
IEEE Symposium on Artificial Life
2018
Corpus ID: 52839973
A long time goal of evolutionary roboticists is to create everincreasing lifelike robots which reflect the important aspects of…
Expand
2017
2017
HyperENTM: Evolving Scalable Neural Turing Machines through HyperNEAT
Jakob Merrild
,
Mikkel Angaju Rasmussen
,
S. Risi
arXiv.org
2017
Corpus ID: 3784100
Recent developments within memory-augmented neural networks have solved sequential problems requiring long-term memory, which are…
Expand
2017
2017
Comparing direct and indirect encodings using both raw and hand-designed features in tetris
Lauren E. Gillespie
,
Gabriel Gonzalez
,
Jacob Schrum
Annual Conference on Genetic and Evolutionary…
2017
Corpus ID: 20350954
Intelligent agents have a wide range of applications in robotics, video games, and computer simulations. However, fully general…
Expand
2015
2015
Feature Learning HyperNEAT: Evolving Neural Networks to Extract Features for Classification of Maritime Satellite Imagery
Phillip Verbancsics
,
Josh Harguess
International Conference on Information…
2015
Corpus ID: 36222930
Imagery analysis represents a significant aspect of maritime domain awareness; however, the amount of imagery is exceeding human…
Expand
2015
2015
Classifying Maritime Vessels from Satellite Imagery with HyperNEAT
Phillip Verbancsics
,
Josh Harguess
Annual Conference on Genetic and Evolutionary…
2015
Corpus ID: 396614
Maritime data uniquely challenges imagery analysis. Such data suffers from degradation, limited samples, and varied formats. To…
Expand
2014
2014
Comparing Adaptivity of Ants using NEAT and rtNEAT
Teo Gelles
,
Mario Sánchez
2014
Corpus ID: 18095055
Although individual ants have an extremely basic intelligence, and are completely incapable of surviving on their own, colonies…
Expand
2013
2013
Do additional CPPN building block functions expand HyperNEATs ability to deal with more complex problems
Cameron May
2013
Corpus ID: 5835374
HyperNEAT is a popular Evolutionary Algorithm used to evolve Artificial Neural Networks. It has been shown that HyperNEAT has…
Expand
2011
2011
Scalable Heterogeneous Multiagent Teams Through Learning Policy Geometry
Kenneth O. Stanley
2011
Corpus ID: 26523660
Abstract : This document is the final technical report for Phase II of the DARPA Computer Science Study Group (CSSG) program…
Expand
2010
2010
Comparison of NEAT and HyperNEAT on a Strategic Decision-Making Problem
Jessica Lowell
,
Kir Birger
,
Sergey Grabkovsky
2010
Corpus ID: 190521
Neuroevolution is a useful machine learning approach for problems with limited domain knowledge, but it has not done well with…
Expand
2010
2010
Evolving Neural Networks for Visual Processing
O. J. Coleman
2010
Corpus ID: 9677816
In this study a recently developed neuroevolution method, HyperNEAT, is applied to new tasks in order to learn more about its…
Expand