Multiple paired forward and inverse models for motor control
Neural Networks - Special issue on neural control and robotics: biology and technology
Embodied artificial intelligence
Artificial Intelligence
Learning to feel the physics of a body
CIMCA '05 Proceedings of the International Conference on Computational Intelligence for Modelling, Control and Automation and International Conference on Intelligent Agents, Web Technologies and Internet Commerce Vol-2 (CIMCA-IAWTIC'06) - Volume 02
Rocking Stamper and Jumping Snakes from a Dynamical Systems Approach to Artificial Life
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Dimensionality reduction through sensory-motor coordination
ICANN/ICONIP'03 Proceedings of the 2003 joint international conference on Artificial neural networks and neural information processing
ICANN '08 Proceedings of the 18th international conference on Artificial Neural Networks, Part I
Exploratory learning structures in artificial cognitive systems
Image and Vision Computing
Guided self-organisation for autonomous robot development
ECAL'07 Proceedings of the 9th European conference on Advances in artificial life
Self-Organizing Sensorimotor Maps Plus Internal Motivations Yield Animal-Like Behavior
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Taming the beast: guided self-organization of behavior in autonomous robots
SAB'10 Proceedings of the 11th international conference on Simulation of adaptive behavior: from animals to animats
Learning new motion primitives in the mirror neuron system: a self-organising computational model
SAB'10 Proceedings of the 11th international conference on Simulation of adaptive behavior: from animals to animats
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Self-organization and the phenomenon of emergence play an essential role in living systems and form a challenge to artificial life systems This is not only because systems become more lifelike, but also since self-organization may help in reducing the design efforts in creating complex behavior systems The present paper studies self-exploration based on a general approach to the self-organization of behavior, which has been developed and tested in various examples in recent years This is a step towards autonomous early robot development We consider agents under the close sensorimotor coupling paradigm with a certain cognitive ability realized by an internal forward model Starting from tabula rasa initial conditions we overcome the bootstrapping problem and show emerging self-exploration Apart from that, we analyze the effect of limited actions, which lead to deprivation of the world model We show that our paradigm explicitly avoids this by producing purposive actions in a natural way Examples are given using a simulated simple wheeled robot and a spherical robot driven by shifting internal masses.