Adaptive algorithms and stochastic approximations
Adaptive algorithms and stochastic approximations
Computational neuroethology: a provisional manifesto
Proceedings of the first international conference on simulation of adaptive behavior on From animals to animats
A possibility for implementing curiosity and boredom in model-building neural controllers
Proceedings of the first international conference on simulation of adaptive behavior on From animals to animats
Natural gradient works efficiently in learning
Neural Computation
Being There: Putting Brain, Body, and World Together Again
Being There: Putting Brain, Body, and World Together Again
Mobile Robot Miniaturisation: A Tool for Investigation in Control Algorithms
The 3rd International Symposium on Experimental Robotics III
Predictability, Complexity, and Learning
Neural Computation
Elements of Information Theory (Wiley Series in Telecommunications and Signal Processing)
Elements of Information Theory (Wiley Series in Telecommunications and Signal Processing)
How the Body Shapes the Way We Think: A New View of Intelligence (Bradford Books)
How the Body Shapes the Way We Think: A New View of Intelligence (Bradford Books)
YARS: A Physical 3D Simulator for Evolving Controllers for Real Robots
SIMPAR '08 Proceedings of the 1st International Conference on Simulation, Modeling, and Programming for Autonomous Robots
Anticipatory Behavior in Adaptive Learning Systems
IJCAI'91 Proceedings of the 12th international joint conference on Artificial intelligence - Volume 1
Adaptive behavior control with self-regulating neurons
50 years of artificial intelligence
ECML'05 Proceedings of the 16th European conference on Machine Learning
Intrinsic Motivation Systems for Autonomous Mental Development
IEEE Transactions on Evolutionary Computation
Open-ended evolutionary robotics: an information theoretic approach
PPSN'10 Proceedings of the 11th international conference on Parallel problem solving from nature: Part I
Empowerment for continuous agent-environment systems
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Electrolocation of multiple objects based on temporal sweep motions
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
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This work presents a novel learning method in the context of embodied artificial intelligence and self-organization, which has as few assumptions and restrictions as possible about the world and the underlying model. The learning rule is derived from the principle of maximizing the predictive information in the sensorimotor loop. It is evaluated on robot chains of varying length with individually controlled, noncommunicating segments. The comparison of the results shows that maximizing the predictive information per wheel leads to a higher coordinated behavior of the physically connected robots compared with a maximization per robot. Another focus of this article is the analysis of the effect of the robot chain length on the overall behavior of the robots. It will be shown that longer chains with less capable controllers outperform those of shorter length and more complex controllers. The reason is found and discussed in the information-geometric interpretation of the learning process.