Topology conserving mappings for learning motor tasks
AIP Conference Proceedings 151 on Neural Networks for Computing
“Fast learning in multi-resolution hierarchies”
Advances in neural information processing systems 1
Connectionist learning for control: an overview
Neural networks for control
Adaptive control using neural networks
Neural networks for control
A framework for the cooperation of learning algorithms
NIPS-3 Proceedings of the 1990 conference on Advances in neural information processing systems 3
Adaptive inverse control
Computation and psychophysics of sensorimotor integration
Computation and psychophysics of sensorimotor integration
Forward models for physiological motor control
Neural Networks - 1996 Special issue: four major hypotheses in neuroscience
A Kendama learning robot based on bi-directional theory
Neural Networks - 1996 Special issue: four major hypotheses in neuroscience
Self-organizing maps
Category learning through multimodality sensing
Neural Computation
Multiple paired forward and inverse models for motor control
Neural Networks - Special issue on neural control and robotics: biology and technology
A tennis serve and upswing learning robot based on bi-directional theory
Neural Networks - Special issue on neural control and robotics: biology and technology
Visually guided movements: learning with modular neural maps in robotics
Neural Networks - Special issue on neural control and robotics: biology and technology
Modular neural net systems, training of
The handbook of brain theory and neural networks
Reaching movements: implications of connectionist models
The handbook of brain theory and neural networks
Internal models in the control of posture
Neural Networks - Special issue on organisation of computation in brain-like systems
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Neural Computation and Self-Organizing Maps; An Introduction
Neural Computation and Self-Organizing Maps; An Introduction
Using Humanoid Robots to Study Human Behavior
IEEE Intelligent Systems
The Knowledge Engineering Review
Variational Learning for Switching State-Space Models
Neural Computation
Equivariant adaptive source separation
IEEE Transactions on Signal Processing
Structured neural networks for pattern recognition
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
SOIM: a self-organizing invertible map with applications in active vision
IEEE Transactions on Neural Networks
Recognition of human head orientation based on artificial neural networks
IEEE Transactions on Neural Networks
Hierarchical overlapped SOM's for pattern classification
IEEE Transactions on Neural Networks
Modular learning schemes for visual robot control
Biomimetic Neural Learning for Intelligent Robots
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The learning of sensory-motor functions have motivated important research works that emphasize a major demand: the combination of multiple neural networks to implement complex functions. A review of a number of works presents some implementations in robotics, describing the purpose of the modular architecture, its structure, and the learning technique that was applied. The second part of the chapter presents an original approach to this problem of network training, proposed by our group. Based on a bi-directional architecture, multiple networks can be trained online with simple local learning rules, while the robotic systems interact with their environment.