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GECCO
2011
Springer
256views Optimization» more  GECCO 2011»
14 years 10 months ago
Evolving complete robots with CPPN-NEAT: the utility of recurrent connections
This paper extends prior work using Compositional Pattern Producing Networks (CPPNs) as a generative encoding for the purpose of simultaneously evolving robot morphology and contr...
Joshua E. Auerbach, Josh C. Bongard
CEC
2009
IEEE
16 years 1 months ago
HyperNEAT controlled robots learn how to drive on roads in simulated environment
Abstract— In this paper we describe simulation of autonomous robots controlled by recurrent neural networks, which are evolved through indirect encoding using HyperNEAT algorithm...
Jan Drchal, Jan Koutník, Miroslav Snorek
ICRA
2007
IEEE
117views Robotics» more  ICRA 2007»
16 years 25 days ago
Predicting Object Dynamics from Visual Images through Active Sensing Experiences
Prediction of dynamic features is an important task for determining the manipulation strategies of an object. This paper presents a technique for predicting dynamics of objects re...
Shun Nishide, Tetsuya Ogata, Jun Tani, Kazunori Ko...
IJCNN
2006
IEEE
16 years 16 days ago
Divide and Conquer Strategies for MLP Training
— Over time, neural networks have proven to be extremely powerful tools for data exploration with the capability to discover previously unknown dependencies and relationships in ...
Smriti Bhagat, Dipti Deodhare
IJCNN
2006
IEEE
16 years 16 days ago
Modeling Cortical Maps with Feed-Backs
Abstract— High-level specification of how the brain represents and categorizes the causes of its sensory input allows to link “what is to be done” (perceptual task) with “...
Thierry Viéville, Pierre Kornprobst