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A Humanoid Robot based on Machine Learning with Incorporation of Vision and Speech Recognition

This paper describes the progress in our project “building a humanoid” robot. There are several approaches by groups that experimented with humanoid robots. Basically, they used common algorithms, which have been known for many years, and very well designed mechanics for sophisticated animation. However, this approach uses rather simple mechanics. The focus is on software development for computer vision, speech recognition and machine learning. For years Multi Value Decomposition has been successfully developed for circuit optimization. Showing that these algorithms can also be adapted to machine learning, the goal will be to demonstrate relational decomposition as a new general purpose machine learning method. Finally, we hope to contribute a new way of thinking to the classical learning methods such as Neuronal Networks and Reinforcement Learning.