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HyperNEAT

Hypercube-based NEAT, or HyperNEAT, is a generative encoding that evolves artificial neural networks (ANNs) with the principles of the widely used… Expand
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Papers overview

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2015
2015
User defined tactics for teams of unmanned systems can be brittle and difficult to define. The state and action space grows with… Expand
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2013
2013
HyperNEAT is a popular indirect encoding method for evolutionary computation that has performed well on a number of benchmark… Expand
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2013
2013
This paper demonstrates that compositional pattern producing networks (CPPNs) can produce phenotypic patterns that exhibit… Expand
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2012
2012
This paper considers the challenge of enabling agents to learn with as little domain-specific knowledge as possible. The main… Expand
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Highly Cited
2011
Highly Cited
2011
Creating gaits for legged robots is an important task to enable robots to access rugged terrain, yet designing such gaits by hand… Expand
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Highly Cited
2011
Highly Cited
2011
A challenging goal of generative and developmental systems (GDS) is to effectively evolve neural networks as complex and capable… Expand
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2011
2011
The recently-introduced evolvable-substrate HyperNEAT algorithm (ES-HyperNEAT) demonstrated that the placement and density of… Expand
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2010
2010
HyperNEAT represents a class of neuroevolutionary algorithms that captures some of the power of natural development with a… Expand
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Highly Cited
2009
Highly Cited
2009
Legged robots show promise for complex mobility tasks, such as navigating rough terrain, but the design of their control software… Expand
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2009
2009
In this paper we present application of genetic programming (GP) [1] to evolution of indirect encoding of neural network weights… Expand
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