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Locomotion / Genetic algorithms / Artificial intelligence / Machine learning / Applied mathematics / HyperNEAT / Neuroevolution / Compositional pattern-producing network / Hexapod / Evolutionary algorithms / Neural networks / Evolutionary computation


Document Date: 2011-09-21 21:44:04

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City

New York / Stockholm / Portland / /

Company

Neural Networks / Autonomous Systems / Sony / AAAI Press / Compositional Pattern Producing Networks / IEEE Press / FT-NEAT / HyperNEAT / Intel / Evolving Large-Scale Neural Networks / /

Country

Germany / Netherlands / Sweden / United States / /

Currency

MMK / USD / /

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Facility

Michigan State University / Lyman Briggs College / /

IndustryTerm

neuroevolutionary algorithms / end product / potential solutions / evolutionary algorithm / neuroevolutionary algorithm / control software / evolutionary algorithms / function networks / multi-agent systems / control systems / /

OperatingSystem

Linux / /

Organization

Michigan State University / National Science Foundation / Lyman Briggs College / Department of Computer Science and Engineering / Congress / United States Army / US Federal Reserve / Department of Philosophy / /

Person

Benjamin E. Beckmann / Jason Gauci / Charles Ofria / Jeff Clune / Luis Zaman / Bradford Book / Ken Stanley / Robert T. Pennock / /

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Position

gait controller / engineer / PID controller / forward / controller / /

Product

Linux / /

ProvinceOrState

Oregon / /

PublishedMedium

Lecture Notes in Computer Science / /

Technology

Technology of Self-Organizing Machines / evolutionary algorithm / Linux / machine learning / NEAT algorithm / neural network / /

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http /

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