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» Explanation-Based Neural Network Learning for Robot Control
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ECAL
2001
Springer
15 years 6 months ago
The Shifting Network: Volume Signalling in Real and Robot Nervous Systems
This paper presents recent work in computational modelling of diffusing gaseous neuromodulators in biological nervous systems. It goes on to describe work in adaptive autonomous sy...
Phil Husbands, Andrew Philippides, Tom Smith, Mich...
GECCO
2007
Springer
217views Optimization» more  GECCO 2007»
15 years 3 months ago
A quantitative analysis of memory requirement and generalization performance for robotic tasks
In autonomous agent systems, memory is an important element to handle agent behaviors appropriately. We present the analysis of memory requirements for robotic tasks including wal...
DaeEun Kim
GECCO
2007
Springer
178views Optimization» more  GECCO 2007»
15 years 8 months ago
Nonlinear dynamics modelling for controller evolution
The problem of how to acquire a model of a physical robot, which is fit for evolution of controllers that can subsequently be used to control that robot, is considered in the con...
Julian Togelius, Renzo De Nardi, Hugo Gravato Marq...
NN
2007
Springer
15 years 1 months ago
Perception through visuomotor anticipation in a mobile robot
Several scientists suggested that certain perceptual qualities are based on sensorimotor anticipation: for example, the softness of a sponge is perceived by anticipating the sensa...
Heiko Hoffmann
GECCO
2009
Springer
15 years 6 months ago
The sensitivity of HyperNEAT to different geometric representations of a problem
HyperNEAT, a generative encoding for evolving artificial neural networks (ANNs), has the unique and powerful ability to exploit the geometry of a problem (e.g., symmetries) by enc...
Jeff Clune, Charles Ofria, Robert T. Pennock