Kinematic networks distributed model for representing and regularizing motor redundancy
Biological Cybernetics
Intelligence without representation
Artificial Intelligence
A bottom-up mechanism for behavior selection in an artificial creature
Proceedings of the first international conference on simulation of adaptive behavior on From animals to animats
Intelligent behaviour in animals and robots
Intelligent behaviour in animals and robots
Multiple paired forward and inverse models for motor control
Neural Networks - Special issue on neural control and robotics: biology and technology
Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
Understanding Intelligence
Proceedings of the Third European Conference on Advances in Artificial Life
Hierarchical dynamical models of motor function
Neurocomputing
Hexapod Walking: an expansion to Walknet dealing with leg amputations and force oscillations
Biological Cybernetics
Crossing Large Gaps: A Simulation Study of Stick Insect Behavior
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
IJCAI'91 Proceedings of the 12th international joint conference on Artificial intelligence - Volume 1
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The capability to behave autonomously is assumed to rely fundamentally on being embedded into the current situation and in the own body. While reactive systems seem sufficient to address these aspects to assure ones surviving in an unpredictable environment, they clearly lack cognitive capabilities as planning ahead: The latter requires internal models which represents the body and the environment and which can be used to mentally simulate behaviours before actually performing one of them. Initially, these models may have evolved in reactive systems to serve specific actions. Cognitive functions may have developed later exploiting the capabilities of these models. We provide a neuronal network approach for such an internal model that can be used as a forward model, an inverse model and a sensor fusion model. It is integrated into a reactive control scheme of a walking machine, enabling the system to plan its actions by mentally simulating them.