TY - SER AU - Wang,Xi-Zhao AU - Yeung,Daniel S. ED - SpringerLink (Online service) TI - International Journal of Machine Learning and Cybernetics SN - 1868-808X CY - Berlin/Heidelberg PB - Springer Berlin Heidelberg, Imprint: Springer. KW - Pattern recognition KW - Systems biology KW - Statistical physics KW - Dynamical systems KW - Computational intelligence KW - Control engineering KW - Robotics KW - Mechatronics KW - Computational Intelligence KW - Artificial Intelligence KW - Control, Robotics, Mechatronics KW - Complex Systems KW - Systems Biology KW - Pattern Recognition N2 - Cybernetics is concerned with describing complex interactions and interrelationships between systems which are omnipresent in our daily life. Machine Learning discovers fundamental functional relationships between variables and ensembles of variables in systems. The merging of the disciplines of Machine Learning and Cybernetics is aimed at the discovery of various forms of interaction between systems through diverse mechanisms of learning from data. The International Journal of Machine Learning and Cybernetics (IJMLC) focuses on the key research problems emerging at the junction of machine learning and cybernetics and serves as a broad forum for rapid dissemination of the latest advancements in the area. The emphasis of IJMLC is on the hybrid development of machine learning and cybernetics schemes inspired by different contributing disciplines such as engineering, mathematics, cognitive sciences, and applications. New ideas, design alternatives, implementations and case studies pertaining to all the aspects of machine learning and cybernetics fall within the scope of the IJMLC. Key research areas to be covered by the journal include: Machine Learning for modeling interactions between systems Pattern Recognition technology to support  discovery of system-environment interaction Control of system-environment interactions Biochemical interaction in biological and biologically-inspired systems Learning for improvement of communication schemes between systems  UR - https://doi.org/10.1007/13042.1868-808X ER -