Document Type

Conference Proceeding

Publication Date



Robots -- Control systems, Artificial intelligence, Machine learning


Relation decomposition has been used for FPGA mapping, layout optimization, and data mining. Decision trees are very popular in data mining and robotics. We present relation decomposition as a new general-purpose machine learning method which generalizes the methods of inducing decision trees, decision diagrams and other structures. Relation decomposition can be used in robotics also in place of classical learning methods such as Reinforcement Learning or Artificial Neural Networks. This paper presents an approach to imitation learning based on decomposition. A Head/Hand robot learns simple behaviors using features extracted from computer vision, speech recognition and sensors.


Originally presented to the 5th International Symposium on Boolean Problems, Freiberg, Germany, in September 2002, and subsequently included in its proceedings.

Persistent Identifier